The numbers are stated judgments. The record began on 15 October 2026 with starting confidences that a model set as the average of five separate readings, from its general knowledge and up to ten developments for each assessment first reported in the three weeks before, after a second model had checked the developments the readings relied on, and a published rule has made every change since. They are not measured probabilities. The question and the rule are fixed before the record begins, and each change shows its evidence and its reasons. The rule and what is not claimed are on the method page.
Demand for AI computing sets the pace of US AI data centre buildout through 2027, with the largest spenders building as fast as the revenue AI earns justifies.
32.5% stated confidence, Unlikely (20–45%). Starting point on the record’s first day: Unlikely (20–45%), 32.5 per cent, the average of five readings, all five of Unlikely. Attention level: For information. Trend: Steady. Activation: Dormant. No recent change has moved toward it.
The judgment as stated before the record began
This is the leading alternative to the main assessment. If the grid is not the binding constraint, the most plausible pace-setter is demand. The largest spenders would build as fast as AI revenue justifies, and connection capacity would go unused when revenue disappoints. Evidence for it would appear first as slowing capital spending, cancellations that cite demand or returns, and falling rental prices for accelerators while projects still find power.
How the record started this assessment
On 15 October 2026, before the record began, a model read the 10 developments below five separate times, first reported in the three weeks before and linked to this assessment's causal factors or to its rivals', and chose a term each time. A second model, from a different family, checked each development a reading relied on, disputed 3 developments, and the five readings were made again without them. The record started the assessment at the average of the five final terms, taken in log-odds: 32.5 per cent, Unlikely (20–45%). Every reading and every check is kept in the first day's record.
The five final readings, in order: Unlikely, Unlikely, Unlikely, Unlikely, Unlikely. Their average, taken in log-odds, is -0.73, a stated confidence of 32.5 per cent. The readings were made by Claude Sonnet 4.6 (Anthropic) and checked by Gemini 4 Argon (Google).
Factors named above: M1 (Waits for large grid connections), M2 (Special terms for large loads: tariffs, deposits and pauses), M3 (Projects delayed, reduced or moved because of power), C1 (Slowing capital spending), C2 (Cancellations and deferrals that cite demand), C3 (Falling rental prices for accelerators), C4 (Spending cut or slowed because AI revenue lags it) and C5 (Power still given as the reason for delays).
The developments shown
- 1. First reported 30 September 2026, 5 independent publishers. Linked to a rival's causal factors.“FERC asks grid operator PJM to revise plan to shield homes from data center costs” · reuters.com · 30 September 2026 · Open the report · archived copy“Biggest US Grid's Data-Center Plan Accepted With 5-Month Pause” · bloomberg.com · 30 September 2026 · Open the report · archived copy“Grid manager delays data center power auction over concern on who gets the bill” · cleveland.com · 1 October 2026 · Open the report · archived copy“Biggest US Grid Suspends Plan for Data Center Power Auction” · energyconnects.com · 5 October 2026 · Open the report · archived copy“PJM Targets 6.8-GW Reliability Gap With Special Backstop Auction — EnergyPulse” · opensentiment.org · 2 October 2026 · Open the report · archived copyAnd 10 more reports of the same development.First round: relied on by 1 reading as counting against it. Second round: relied on by 4 readings as counting against it.
- Check of its use as counting against the assessment: Upheld by the second model, run on Gemini 4 Argon (Google).
Its reason, as the model wrote it: The reports confirm that FERC suspended PJM's data center power procurement plan for five months to ensure large new loads bear the costs of their demand amid a 6.8-GW capacity shortfall. This regulatory pause and imposition of cost-allocation terms for large loads strengthens factor M2 (special terms and pauses for large loads) and M1 (waits and delays for grid capacity), which supports the main grid-constraint thesis and therefore counts against the rival assessment that AI demand sets the pace of buildout.
- Report 1, quoted: “FERC accepted key elements of PJM’s proposed power procurement but delayed implementation for five months and ordered revisions to ensure data centers and other large new users bear costs attributable to their demand.”
- Report 5, quoted: “rapid demand gains, driven primarily by data center construction, outpaced available supply in its latest auction results.”
- 2. First reported 8 October 2026, 4 independent publishers. Linked to a rival's causal factors.“PJM Fast-Tracks 2.1 GW Capacity to Meet Rising Demand — EnergyPulse” · opensentiment.org · 10 October 2026 · Open the report · archived copy“PJM accepts two ENGIE batteries and a gas uprate on its fast track | The Duck Curve” · theduckcurve.com · 9 October 2026 · Open the report · archived copy“PJM fast track approves first 2.1 GW: Engie storage, LS Power gas uprate — Grid Brief” · gridbrief.org · 10 October 2026 · Open the report · archived copy“PJM approves first 3 expedited interconnection projects” · globalenergyreport.com · 8 October 2026 · Open the report · archived copyFirst round: relied on by no reading. Second round: relied on by no reading.No reading relied on it, so it was not checked.
- 3. First reported 7 October 2026, 4 independent publishers. Linked to a rival's causal factors.“Duke Energy protects customers from data center costs” · wowktv.com · 7 October 2026 · Open the report · archived copy“Duke Energy strikes deal with data center giants” · axios.com · 7 October 2026 · Open the report · archived copy“Duke Energy Corporation - Duke Energy protects customers from data center costs” · investors.duke-energy.com · 7 October 2026 · Open the report · archived copy“FERC approves Duke large load transmission rules despite cost-shift concerns” · utilitydive.com · 13 October 2026 · Open the report · archived copyFirst round: relied on by no reading. Second round: relied on by 1 reading as counting against it.No reading relied on it, so it was not checked.
- 4. First reported 25 September 2026, 4 independent publishers. Linked to a rival's causal factors.“FERC rejects Oklo complaint seeking to reinstate project in PJM interconnection study cycle” · utilitydive.com · 25 September 2026 · Open the report · archived copy“FERC rejects Oklo's bid to put a 750 MW project back in PJM's queue — Grid Brief” · gridbrief.org · 26 September 2026 · Open the report · archived copy“FERC Rejects Oklo Bid to Restore 750 MW Project to PJM Queue – American Buildout” · americanbuildout.com · 25 September 2026 · Open the report · archived copy“FERC Backs PJM on Oklo Virginia Project, Finding No Rules Breach — EnergyReader.io” · energyreader.io · 29 September 2026 · Open the report · archived copyFirst round: relied on by no reading. Second round: relied on by 1 reading as counting against it.No reading relied on it, so it was not checked.
- 5. First reported 8 October 2026, 3 independent publishers. Linked to a rival's causal factors.“Energy Department Supports FERC’s Call for PJM to Protect Ratepayers and Build More Reliable Power | Department of Energy” · energy.gov · 8 October 2026 · Open the report · archived copy“DOE presses PJM on ratepayer protections from large load costs | Utility Dive” · utilitydive.com · 8 October 2026 · Open the report · archived copy“DOE Presses PJM On Ratepayer Protections From Large Load Costs” · zerohedge.com · 9 October 2026 · Open the report · archived copyFirst round: relied on by no reading. Second round: relied on by 2 readings as counting against it.No reading relied on it, so it was not checked.
- 6. First reported 2 October 2026, 3 independent publishers. Linked to this assessment's own causal factors.“Oracle's $Multi-Billion AI Data Center in Wisconsin Faces Years of Delays Over Power Grid Approvals” · webpronews.com · 2 October 2026 · Open the report · archived copy“PSC wipes out 10 months of progress on Oracle's 1.3 GW Wisconsin data center — pushing partial 310 MW power to late 2027 and full load to 2029” · techradar.com · 4 October 2026 · Open the report · archived copy“Oracle's Wisconsin AI data center hits a Wisconsin power line roadblock” · startupfortune.com · 5 October 2026 · Open the report · archived copyFirst round: relied on by 5 readings as counting against it. Second round: relied on by 5 readings as counting against it.
- Check of its use as counting against the assessment: Upheld by the second model, run on Gemini 4 Argon (Google).
Its reason, as the model wrote it: The reports explicitly state that Oracle's 1.3 GW AI data center in Wisconsin faces years of delays due to power grid and transmission infrastructure approvals, pushing partial power to late 2027 and full load to 2029. This directly strengthens factor C5 (Power still given as the reason for delays), which undercuts the assessment that demand sets the pace of buildout rather than grid power.
- Report 1, quoted: “Oracles $Multi-Billion AI Data Center in Wisconsin Faces Years of Delays Over Power Grid Approvals”
- Report 2, quoted: “PSC wipes out 10 months of progress on Oracles 1.3 GW Wisconsin data center — pushing partial 310 MW power to late 2027 and full load to 2029”
- 7. First reported 14 October 2026, 1 independent publisher. Linked to this assessment's own causal factors.“Data Center Physical Infrastructure Market Grows 27 Percent Y/Y To $14 Billion In 2Q 2026, According To Dell'Oro Group” · menafn.com · 14 October 2026 · Open the report · archived copyFirst round: relied on by no reading. Second round: relied on by 5 readings as counting against it.No reading relied on it, so it was not checked.
- 8. First reported 13 October 2026, 1 independent publisher. Linked to this assessment's own causal factors.“Utilities Struggle to Confront Issue of ‘Phantom' AI Data Centers” · breitbart.com · 13 October 2026 · Open the report · archived copyFirst round: relied on by 2 readings as support for the assessment. Removed from the second round, because the second model disputed it.
- Check of its use as support for the assessment: Disputed by the second model, so the second round was read without it, run on Gemini 4 Argon (Google).
Its reason, as the model wrote it: The reading uses this development as supporting the assessment that demand sets the pace, yet it was only linked to factors C5 (which undercuts this assessment when stronger) and M1 (which supports the rival assessment that grid power is the binding constraint). Moreover, the report itself states that speculative requests are swelling grid queues and illustrating how power access and interconnection delay AI infrastructure, which reinforces C5 and M1 against this assessment rather than supporting it.
Its ground: what the reports state is not a change in this causal factor.- Report 1, quoted: “Utilities Struggle to Confront Issue of ‘Phantom AI Data Centers”
- Report 1, quoted: “Utilities are tightening connection requirements as speculative data-center requests swell grid queues, illustrating how power access and interconnection—not just chips—can delay AI infrastructure.”
- 9. First reported 11 October 2026, 1 independent publisher. Linked to this assessment's own causal factors.“Big Tech GPU supplies run dry as neoclouds expand” · g-enews.com · 11 October 2026 · Open the report · archived copyFirst round: relied on by 4 readings as counting against it. Removed from the second round, because the second model disputed it.
- Check of its use as counting against the assessment: Disputed by the second model, so the second round was read without it, run on Gemini 4 Argon (Google).
Its reason, as the model wrote it: The report describes GPU shortages and rising rental prices as neoclouds expand, rather than projects slipping or being delayed because of power. The reading itself notes that this development is about 'no spare accelerator capacity and no falling rental prices' (which it calls C3), so it does not represent a change in factor C5 ('Power still given as the reason for delays'). Even the summary's mention that 'data-center power infrastructure lags' is framed as a reason GPU supply constraints could persist, not as a report of data centre project delays attributed to grid power.
Its ground: what the reports state is not a change in this causal factor.- Report 1, quoted: “Big Tech GPU supplies run dry as neoclouds expand”
- Report 1, quoted: “intense competition for NVIDIA GPUs, rising rental prices, and supply constraints that could persist as data-center power infrastructure lags.”
- 10. First reported 8 October 2026, 1 independent publisher. Linked to this assessment's own causal factors.“The AI Giants Are Facing a Severe Case of Financial Indigestion” · bloomberg.com · 8 October 2026 · Open the report · archived copyFirst round: relied on by 3 readings as support for the assessment. Removed from the second round, because the second model disputed it.
- Check of its use as support for the assessment: Disputed by the second model, so the second round was read without it, run on Gemini 4 Argon (Google).
Its reason, as the model wrote it: The reading relied on this development as supporting the assessment if_wrong (that demand sets the pace), noting that 'financial indigestion among AI giants' could weakly support it. However, the development was linked only to factors C5 and M3, both of which concern power and grid delays acting as the binding constraint (where a stronger factor undercuts if_wrong and supports main). Neither financial indigestion nor lengthy grid-connection timelines constitutes a change in C5 or M3 that bears on the assessment if_wrong in a supporting direction.
Its ground: what the reports state is not a change in this causal factor.- Report 1, quoted: “The AI Giants Are Facing a Severe Case of Financial Indigestion”
- Report 1, quoted: “AI data-center projects face equipment and labor shortages, permitting and community opposition, and lengthy grid-connection timelines, highlighting constraints on planned buildouts.”
The readings, and their reasons
The first round, before the check
- Reading 1: Unlikely (20–45%), from 10 developments shown. It relied on development 6 as counting against the assessment, development 8 as support for the assessment, development 9 as counting against the assessment.
Its reason, as the model wrote it: Development 6 (Oracle's Wisconsin centre delayed years by power grid approvals, C5 counts against) and developments linked through the rival assessment such as the FERC and PJM actions all point to power as the active constraint rather than demand softness. Development 8 reports utilities struggling with phantom data centres that never materialize, which offers some support to C2 and C4, but it is a single source. Development 9 reports GPU supplies running dry at neoclouds (C3 counts against, as this implies no spare accelerator capacity and no falling rental prices). The weight of evidence shows the grid binding before demand softens, making this assessment unlikely.
- Reading 2: Unlikely (20–45%), from 10 developments shown. It relied on development 6 as counting against the assessment, development 8 as support for the assessment, development 10 as support for the assessment.
Its reason, as the model wrote it: Development 6 reports Oracle's 1.3 GW Wisconsin data centre pushed to late 2027 at the earliest for partial power and 2029 for full load due to grid approval delays, directly countering C5 and showing power as the stated reason for delay. Development 8 reports utilities struggling with phantom AI data centres, suggesting some speculative demand but not a broad demand-led slowdown. Development 10 notes financial indigestion among AI giants, which could weakly support C4, but is a single-source opinion piece. The clearest multi-source evidence points to power as the binding reason for project delays rather than demand softness, making the demand-pacing alternative unlikely but not very unlikely given some real financing tensions.
- Reading 3: Unlikely (20–45%), from 10 developments shown. It relied on development 6 as counting against the assessment, development 10 as support for the assessment, development 9 as counting against the assessment.
Its reason, as the model wrote it: Development 6 (if_wrong's own factor) reports Oracle's Wisconsin data centre facing years of delays specifically because of grid approval problems, which directly supports C5 (power still given as the reason for delays) and counts against this assessment. Development 10 reports AI giants facing financial indigestion, touching on C4, but does not show a spending cut attributed to lagging AI revenue. Development 9 reports GPU supplies running dry as neoclouds expand, pointing toward accelerator scarcity as a possible rival constraint (C3 direction absent, but supply pressure weakens the spare-capacity signal). The developments overall show power constraints still actively causing project slippage, which is the strongest signal against a demand-paced scenario, keeping this assessment unlikely.
- Reading 4: Unlikely (20–45%), from 10 developments shown. It relied on development 6 as counting against the assessment, development 1 as counting against the assessment, development 9 as counting against the assessment.
Its reason, as the model wrote it: Development 6 directly reports Oracle's Wisconsin data centre delayed by years because of power grid approvals, a concrete case where power rather than demand slows buildout (counts against via C5). Development 1, linked through the rival, shows PJM's large-load plan paused over interconnection cost disputes, reinforcing that the grid still binds (counts against via C5). Development 3, also linked through the rival, shows Duke imposing special terms on data centres rather than any report of projects paused for demand reasons, weakening the demand-pacing story. Development 9 notes GPU supplies running dry as neoclouds expand, suggesting capacity is being absorbed rather than sitting idle, which is inconsistent with a demand shortfall (counts against via C3). No development reports cancellations or deferrals citing insufficient AI revenue or overcapacity.
- Reading 5: Unlikely (20–45%), from 10 developments shown. It relied on development 10 as support for the assessment, development 9 as counting against the assessment, development 6 as counting against the assessment.
Its reason, as the model wrote it: The developments linked to this assessment's own factors are thin and mixed. Development 10 describes financial indigestion at AI giants, which touches C4, but it is a single source and does not report an actual spending cut or a stated demand-driven rationale for slowing. Development 9 reports GPU supplies running dry as neoclouds expand, which counts against C3 and against spare-capacity signals this scenario requires. Development 6, linked through the rival, shows Oracle's Wisconsin campus facing years of power-related delays, directly supporting C5 and cutting against the demand-pacing story. The bulk of the grid-side developments across all three assessments points to power as the active constraint rather than demand softness, leaving this alternative unlikely relative to the main assessment.
The second round, after the check, which set the start
- Reading 1: Unlikely (20–45%), from 7 developments shown. It relied on development 6 as counting against the assessment, development 7 as counting against the assessment, development 1 as counting against the assessment, development 3 as counting against the assessment, development 5 as counting against the assessment.
Its reason, as the model wrote it: Development 7 reports strong 27 percent year-on-year growth in data centre physical infrastructure spending, counting against C1. Development 6 reports Oracle's Wisconsin campus delayed specifically because of power grid approvals, directly supporting C5 and showing the grid still binds. Developments 1, 3 and 5, linked through the rival's factors, also reinforce that power rather than demand is the operative constraint. No development shows cancellations citing demand shortfalls or falling accelerator prices that would support C2 or C3.
- Reading 2: Unlikely (20–45%), from 7 developments shown. It relied on development 6 as counting against the assessment, development 7 as counting against the assessment.
Its reason, as the model wrote it: Development 6 (Oracle's 1.3 GW Wisconsin data centre pushed to late 2027 and full load to 2029 because of power grid approval delays) directly supports C5, showing power still given as the reason for project delays and thereby undercutting this assessment. Development 7 (data centre physical infrastructure market growing 27 percent year on year to $14 billion in Q2 2026) points to continued strong demand-driven spending rather than a demand-paced slowdown, counting against C1. Developments linked through the rival assessment (Duke Energy special terms, PJM pause, FERC proceedings) all reinforce the grid-constraint story rather than a demand-paced one. No development shown supports C2, C3 or C4.
- Reading 3: Unlikely (20–45%), from 7 developments shown. It relied on development 6 as counting against the assessment, development 7 as counting against the assessment, development 1 as counting against the assessment, development 4 as counting against the assessment, development 5 as counting against the assessment.
Its reason, as the model wrote it: Development 6 reports the Oracle Wisconsin campus delayed by years because of power-grid approvals, which directly counts against this assessment via its C5 factor. Development 7 shows the data centre physical infrastructure market growing 27 percent year on year, pointing to continued expansion rather than a demand-paced slowdown. Developments 1, 4 and 5 linked through the rival's factors all point to active grid constraints still binding projects, weakening the case that demand rather than power is the pace-setter. No development cited here shows cancellations or deferrals attributable to weak AI revenue or spare accelerator capacity.
- Reading 4: Unlikely (20–45%), from 7 developments shown. It relied on development 6 as counting against the assessment, development 1 as counting against the assessment, development 7 as counting against the assessment.
Its reason, as the model wrote it: Development 6, linked through a rival factor, reports that Oracle's 1.3 GW Wisconsin data centre faces years of delays because of power grid approvals, directly supporting C5 and counting against this assessment. Development 1, also linked through a rival factor, shows PJM delaying its large-load capacity auction over grid-cost concerns, further supporting C5. Development 7 shows the physical infrastructure market growing 27 percent year on year, giving no sign of slowing capital spending that would support C1. The overall picture is that power remains the stated bottleneck rather than demand, which is what weakens the demand-pacing scenario.
- Reading 5: Unlikely (20–45%), from 7 developments shown. It relied on development 6 as counting against the assessment, development 1 as counting against the assessment, development 7 as counting against the assessment.
Its reason, as the model wrote it: Development 6 (Oracle's Wisconsin data center pushed to 2029 for full power because of grid approvals) is a direct report of power causing delay, which weakens this assessment via factor C5. Developments 1, 3 and 5 (linked through the rival) all show ongoing regulatory and tariff actions treating grid capacity as scarce and contested, further indicating the grid still binds rather than demand being the pace-setter (factor C5). Development 7 shows the physical infrastructure market growing 27 percent year on year, pointing against any demand-led slowdown (factor C1). The few developments shown are consistent and point away from this assessment.
Readings made before this one
No starting point was read before this one, as the first day records.
Causes of uncertainty
- Demand and power can bind in different places at the same time, so national figures can hide a regional constraint.
- Rental prices for accelerators are partly set by list prices that change rarely, so they may lag a change in demand.
- A slowdown in spending can reflect cheaper computation rather than weaker demand.
What would change the judgment
- Several of the largest spenders cutting capital spending while their projects are reported to have power available.
- Cancellations and lease exits that cite demand, returns or overcapacity rather than power.
- Sustained falls in rental prices for accelerators across the major providers.
The causal factors, and which way each one cuts
| Factor | Which way it cuts | What evidence looks like | Last moved |
|---|---|---|---|
| C1. Slowing capital spending A slowdown in the growth of the largest spenders' capital spending, quarter on quarter or year on year. Slowing spending while power is available points to demand as the pace-setter. Public data that could later test this factor: quarterly payments for property and equipment by Microsoft and Meta, from their SEC filings. Not yet used as a test. | Supports. A stronger factor supports the assessment. |
| Not yet |
| C2. Cancellations and deferrals that cite demand Projects paused, cancelled or deferred where the stated reason is demand, returns or overcapacity rather than power. | Supports. A stronger factor supports the assessment. |
| Not yet |
| C3. Falling rental prices for accelerators Price cuts for rented accelerator capacity at the major cloud and specialized GPU providers. Falling prices point to spare capacity, which a market paced by demand would show. Public data that could later test this factor: the hourly price of an H100 virtual machine on Microsoft Azure, in the regions US East and US East 2. Not yet used as a test. | Supports. A stronger factor supports the assessment. |
| Not yet |
| C4. Spending cut or slowed because AI revenue lags it The largest spenders cutting or slowing their planned capital spending, and giving as the reason that the revenue they earn from AI has not kept pace with it. A cut made for that reason shows spending following AI revenue, which this assessment expects. Spending that keeps rising while AI revenue lags behind it shows the opposite, and weakens this assessment. The factor is the reason given for a company's spending plans as a whole. The size of the reported spending, and the fate of a single project, are separate factors. | Supports. A stronger factor supports the assessment. |
| Not yet |
| C5. Power still given as the reason for delays Continued reports that projects slip because of power. These mean the grid still binds, which weakens this scenario. | Weakens. A stronger factor weakens the assessment. |
| Not yet |
What the assessment assumes, and what would break it
- CA1. The largest spenders pace AI capacity to the returns they can see.If this fails, the assessment fails.
Invalidated if Microsoft, Alphabet, Amazon and Meta together raise quarterly payments for property and equipment year over year in two consecutive quarters in which their combined operating income falls year over year, as filed with the SEC (XBRL concepts PaymentsToAcquirePropertyPlantAndEquipment for Microsoft, Alphabet and Meta, and PaymentsToAcquireProductiveAssets for Amazon, with year-to-date figures differenced into quarters and the fourth quarter taken as the annual figure less nine months, and OperatingIncomeLoss).
Source: SEC EDGAR XBRL company facts. The criterion’s fingerprint was fixed on 15 October 2026 and is part of the record’s first day. - CA2. A slowdown led by demand would show in signed commitments before it shows in spending.If this fails, the assessment weakens.
Invalidated if the combined quarterly payments for property and equipment of Microsoft, Alphabet, Amazon and Meta (XBRL concepts PaymentsToAcquirePropertyPlantAndEquipment for Microsoft, Alphabet and Meta, and PaymentsToAcquireProductiveAssets for Amazon, with year-to-date figures differenced into quarters and the fourth quarter taken as the annual figure less nine months) fall year over year in a quarter that follows two consecutive quarters in which the combined total of the amounts each company discloses in its 10-Q or 10-K as leases not yet commenced at the balance-sheet date (for Amazon, the “Leases not yet commenced” row of its commitments table) grew.
Source: SEC EDGAR, quarterly and annual filings. The criterion’s fingerprint was fixed on 15 October 2026 and is part of the record’s first day.
The rival explanations
Evidence moves the assessment only when it bears differently on the assessment than on at least one of these. Evidence that fits them equally carries no weight.
- CX1. Demand softens but power still binds locally: a slowdown shows up as fewer new connection requests rather than as faster completion of those already waiting.No development was recorded on this assessment in the last 7 days.Favoured by:
- Connection queues shrink while waiting times stay long.
- Spending slows in regions with spare power but not where power is scarce.
Ruled out by:- Waiting times for connection fall as spending slows.
- CX2. Cheaper computation slows spending, because a falling cost per unit of AI output lets the largest spenders build less while use of AI services keeps growing.No development was recorded on this assessment in the last 7 days.Favoured by:
- Reported growth in the use of AI services alongside slower capital spending.
- The largest providers announce a falling cost per unit of AI output.
Ruled out by:- Use of AI services and capital spending fall together.
A development is recorded when the rule applies it to the assessment or sets it aside. Each count comes from the readings sealed with the changes, and a development set aside as fitting every alternative equally tells no alternative apart.
Evidence behind changes in the last 30 days
Each item is a report or data series cited by a sealed change on this assessment. The update loop reads headlines and summaries, and no summary is shown as the evidence.
No evidence has been cited in the last 30 days.
Evidence considered and set aside
Developments the update loop read in the last 30 days and set aside because they fitted this assessment and each of its rival explanations equally. Under the rule such evidence carries no weight, so none of it moved anything.
Nothing on this assessment was set aside in the last 30 days.
Changes to this assessment
No change to this assessment yet.
The rest of the judgment
The question’s text on this page is as sealed on the record’s first day. Fingerprint . Fingerprint pending. Records are fingerprinted each day at 23:59 UTC.