AI data centres (version 2) · All records

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.

This record corrects the first record of the same question, AI data centres, which began on 12 October 2026 and continues unchanged under the rules it began with. What changed, and why is on this record’s method page.

The condition it rests on

Capital spending on AI infrastructure by the largest US cloud companies keeps rising through 2027, so demand keeps pressing on the power constraint.

67.5% stated confidence, Likely (55–80%). Starting point on the record’s first day: Likely (55–80%), 67.5 per cent, the average of five readings, all five of Likely. Attention level: For information. Trend: Steady.

Stated confidence in the one daily state so far: 15 October 2026, 67.5 per cent. A chart is drawn once there are 3 daily states.

Key judgment

The judgment as stated before the record began

The main assessment holds only while demand keeps pressing on the grid. The clearest public measure of that pressure is what the largest cloud companies spend on property and equipment. Those figures are filed quarterly with the SEC and cannot be revised without a public filing. The assessment would weaken if spending stopped growing year over year, if several of the largest spenders cut their outlook in the same season, or if leases they have signed but not yet started began to shrink.

Starting point

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: 67.5 per cent, Likely (55–80%). Every reading and every check is kept in the first day's record.

The five final readings, in order: Likely, Likely, Likely, Likely, Likely. Their average, taken in log-odds, is 0.73, a stated confidence of 67.5 per cent. The readings were made by Claude Sonnet 4.6 (Anthropic) and checked by Gemini 4 Argon (Google).

Factors named above: R1 (Quarterly capital spending by the largest US cloud companies), R2 (Capital spending outlook) and R3 (Financing for data centre campuses).

The developments shown

1. First reported 13 October 2026, 1 independent publisher. Linked to this assessment's own causal factors.
“Alphabet Signals More AI Spending After $80.6 Billion First-Half Outlay” · tokenpost.com · 13 October 2026 · Open the report · archived copy
First round: relied on by 5 readings as support for the assessment. Second round: relied on by 5 readings as support for the assessment.
- Check of its use as support for the assessment: Upheld by the second model, run on Gemini 4 Argon (Google).
  Its reason, as the model wrote it: Report 1 explicitly states that Alphabet, one of the largest US cloud companies, spent $80.6 billion in the first half of 2026 and signaled a significant increase in capital expenditure in 2027. This directly reflects strong current capital spending (factor R1) and a rising capital spending outlook (factor R2), supporting the assessment over alternatives RX1 and RX2.
  - Report 1, quoted: “Alphabet Signals More AI Spending After $80.6 Billion First-Half Outlay”
  - Report 1, quoted: “Alphabet signaled a significant increase in capital expenditure in 2027 after spending $80.6 billion in the first half of 2026”
2. First reported 13 October 2026, 1 independent publisher. Linked to this assessment's own causal factors.
“Fermi Signs Credit Support Agreement with AMD and Announces Partnership” · digitaljournal.com · 13 October 2026 · Open the report · archived copy
First 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 13 October 2026, 1 independent publisher. Linked to this assessment's own causal factors.
“Hyperscale Data Reduces ATM Program, Shifts to Debt” · tipranks.com · 13 October 2026 · Open the report · archived copy
First round: relied on by 1 reading 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: Factor R3 covers debt, lease, and joint-venture financing for data centre campuses, where securing debt financing supports the assessment and withdrawn or repriced financing counts against it. The report states that Hyperscale Data is shifting from an at-the-market equity program to project debt to fund a 20 MW Michigan buildout, which is an move toward using project debt rather than a financing withdrawal or setback that weakens R3. Accordingly, the reported development does not bear on R3 against the assessment.
  Its ground: what the reports state is not a change in this causal factor.
  - Report 1, quoted: “Hyperscale Data Reduces ATM Program, Shifts to Debt”
  - Report 1, quoted: “Hyperscale Data plans to use project debt to help fund a Michigan AI data-center buildout designed to provide 20 MW of compute capacity for a neocloud customer.”
4. First reported 12 October 2026, 1 independent publisher. Linked to this assessment's own causal factors.
“SOAR AI Secures Up to $1 Billion Equity Facility to Fund Expansion of Its AI Infrastructure Platform” · businesswire.com · 12 October 2026 · Open the report · archived copy
First round: relied on by 1 reading 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 report describes a specialized AI infrastructure provider (SOAR AI) securing external financing to develop an AI campus and GPU clusters backed by customer orders, rather than capital spending on the balance sheet of one of the largest US cloud companies. This development fits alternative RX2—that spending moves off the largest companies' balance sheets to specialized providers—at least as well as it supports the main assessment.
  Its ground: it fits one of the rival explanations as well as the assessment.
  - Report 1, quoted: “SOAR AI Secures Up to $1 Billion Equity Facility to Fund Expansion of Its AI Infrastructure Platform”
  - Report 1, quoted: “SOAR AI announced an equity facility of up to $1 billion to develop its Ohio AI campus and other sites, including dedicated GPU clusters backed by customer orders.”
5. First reported 11 October 2026, 1 independent publisher. Linked to this assessment's own causal factors.
“Alphabet's Google Cloud Is Surging at 82%, and the Heavy Spending Is Starting to Make Sense” · theglobeandmail.com · 11 October 2026 · Open the report · archived copy
First round: relied on by 4 readings as support for the assessment. Second round: relied on by 3 readings as support for the assessment.
- Check of its use as support for the assessment: Upheld by the second model, run on Gemini 4 Argon (Google).
  Its reason, as the model wrote it: The report directly states that Alphabet guided to $195–205 billion in 2026 capital expenditure, driven by strong cloud demand and a large backlog. This provides evidence of a large US cloud company's capital spending outlook (factor R2) supporting continued high spending rather than leveling off or moving off-balance-sheet.
  - Report 1, quoted: “Alphabets Google Cloud Is Surging at 82%, and the Heavy Spending Is Starting to Make Sense”
  - Report 1, quoted: “The report says Alphabet guided to $195–205 billion in 2026 capital expenditure and cited strong cloud demand and a large backlog, while noting that supply is limiting its ability to meet demand.”
6. First reported 8 October 2026, 1 independent publisher. Linked to this assessment's own causal factors.
“AWS CEO Matt Garman defends AI spending with a spread-out customer base” · cryptobriefing.com · 8 October 2026 · Open the report · archived copy
First round: relied on by 4 readings as support for the assessment. Second round: relied on by 5 readings as support for the assessment.
- Check of its use as support for the assessment: Upheld by the second model, run on Gemini 4 Argon (Google).
  Its reason, as the model wrote it: Report 1 directly states that AWS CEO Matt Garman is defending massive AI infrastructure expenditure as Amazon plans roughly $220 billion in 2026 capital spending. This confirms rising capital spending on AI infrastructure by one of the largest US cloud companies, supporting the assessment and directly countering the alternatives of flat or off-balance-sheet spending.
  - Report 1, quoted: “AWS CEO Matt Garman defends AI spending with a spread-out customer base”
  - Report 1, quoted: “the company plans roughly $220 billion in 2026 capital spending”
  - Report 1, quoted: “Amazon Web Services is about to spend an enormous amount of money on AI infrastructure.”
7. First reported 6 October 2026, 1 independent publisher. Linked to this assessment's own causal factors.
“Distress Watch: Data Center Debt Selloff Snags AI Buildouts” · news.bloomberglaw.com · 6 October 2026 · Open the report · archived copy
First 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: Report 1 explicitly states that a selloff in data center debt is snagging AI buildouts and adding financing risk to AI infrastructure expansion. This directly reflects friction in debt financing for data center campuses (Factor R3), where withdrawn or repriced financing bears against the factor, and thus counts against the assessment.
  - Report 1, quoted: “Distress Watch: Data Center Debt Selloff Snags AI Buildouts”
  - Report 1, quoted: “Bloomberg Law reports that data-center debt is selling off amid heightened scrutiny, including concerns about permitting delays, adding financing risk to AI infrastructure expansion.”
8. First reported 6 October 2026, 1 independent publisher. Linked to this assessment's own causal factors.
“The AI capex ledger: hyperscaler spending versus cloud revenue, 2024 to 2026 | BlockWest Research” · blockwest.co · 6 October 2026 · Open the report · archived copy
First round: relied on by 1 reading 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 reading treats this development as counting against the assessment via factor R1. However, R1 measures quarterly capital spending by the largest US cloud companies, where growth supports the assessment. The report shows an 87% year-over-year increase in property and equipment spending by Microsoft, Alphabet, Amazon, and Meta, which strengthens R1 in favor of the assessment rather than counting against it.
  Its ground: what the reports state is not a change in this causal factor.
  - Report 1, quoted: “Microsoft, Alphabet, Amazon and Meta spent a combined $165.1B on property and equipment in calendar Q2 2026, up 87% from $88.2B a year earlier”
  - Report 1, quoted: “Cloud revenue is accelerating but remains far smaller than the spend: Google Cloud grew 82% to $24.8B and AWS 37% to $42.2B in Q2 2026, while Alphabet’s quarterly capex was 1.8 times Google Cloud revenue.”
9. First reported 5 October 2026, 1 independent publisher. Linked to this assessment's own causal factors.
“The Core Hyperscaler Battle: First-Mover Software Integration Vs. Raw Infrastructure Scale - AOL” · aol.com · 5 October 2026 · Open the report · archived copy
First round: relied on by no reading. Second round: relied on by no reading.
No reading relied on it, so it was not checked.
10. First reported 3 October 2026, 1 independent publisher. Linked to this assessment's own causal factors.
“Who is paying for the AI data center boom?” · thesuperintelligencenews.com · 3 October 2026 · Open the report · archived copy
First round: relied on by no reading. Second round: relied on by 1 reading as support for the assessment.
No reading relied on it, so it was not checked.

The readings, and their reasons

The first round, before the check

Reading 1: Likely (55–80%), from 10 developments shown. It relied on development 1 as support for the assessment, development 5 as support for the assessment, development 6 as support for the assessment, development 7 as counting against the assessment.
Its reason, as the model wrote it: Development 1 shows Alphabet signaling more AI spending after an $80.6 billion first-half outlay (R1 and R2 support). Development 5 reports Google Cloud surging at 82 percent and heavy spending starting to make sense (R1 supports). Development 6 shows AWS CEO defending continued AI spending with a broad customer base (R2 supports). Development 7 notes a data-centre debt selloff that snags some AI buildouts, which introduces modest financing friction (R3 counts against slightly), but the overall picture of the largest cloud spenders remains one of rising committed capital through the period. The developments are modest in number but the prior evidence of multi-year capex commitments by the hyperscalers is strong.
Reading 2: Likely (55–80%), from 10 developments shown. It relied on development 1 as support for the assessment, development 5 as support for the assessment, development 6 as support for the assessment, development 7 as counting against the assessment, development 3 as counting against the assessment.
Its reason, as the model wrote it: Development 1 signals Alphabet's continued heavy AI capital spending after an $80.6 billion first-half outlay, supporting R1 and R2. Development 5 shows Google Cloud surging at 82 percent with analysts saying heavy spending is starting to make sense, supporting R2. Development 6 reports AWS CEO defending ongoing AI spending with a broad customer base, supporting R2. Development 7 flags a data centre debt selloff snagging some AI buildouts, which weakly undercuts R3, and development 3 notes one player reducing its ATM programme and shifting to debt, a mild caution on financing. The broad picture from multiple sources is that the largest spenders are maintaining and signalling further growth in capital spending, keeping demand pressed against the power constraint.
Reading 3: Likely (55–80%), from 10 developments shown. It relied on development 1 as support for the assessment, development 5 as support for the assessment, development 7 as counting against the assessment, development 8 as counting against the assessment.
Its reason, as the model wrote it: Development 1 reports Alphabet signalling more AI spending after an $80.6 billion first-half outlay, directly supporting factor R1 and R2. Development 5 reports Google Cloud surging at 82 percent year on year with heavy spending starting to make sense, further supporting R1 and R2. Development 7 flags a data centre debt selloff that is snagging some AI buildouts, which touches on financing stress and counts against R3. Development 10 raises questions about who is paying for the AI data centre boom, and development 8 compares hyperscaler capex against cloud revenue showing spending outpacing revenue, together providing mild caution. On balance the largest spenders are publicly committing to continued growth in capital spending, so demand keeps pressing on the power constraint, but financing stress introduces enough uncertainty to keep the term at likely rather than very likely.
Reading 4: Likely (55–80%), from 10 developments shown. It relied on development 1 as support for the assessment, development 5 as support for the assessment, development 6 as support for the assessment, development 7 as counting against the assessment.
Its reason, as the model wrote it: Development 1 from the rests_on set shows Alphabet signalling continued AI spending after an $80.6 billion first-half outlay, supporting rising capital expenditure (supports via R2). Development 5 reports Google Cloud surging at 82 percent and heavy spending starting to make financial sense, reinforcing a raised outlook (supports via R2). Development 6 shows the AWS CEO defending continued AI spending with a broad customer base, supporting sustained outlays (supports via R2). Development 7 flags a data-centre debt selloff snagging some buildouts, a mild caution (counts against via R3), but it is a single report and the broader set of developments shows major hyperscalers pressing forward. The overall picture from widely known prior spending trajectories plus these developments supports the condition that demand keeps pressing on the power constraint.
Reading 5: Likely (55–80%), from 10 developments shown. It relied on development 1 as support for the assessment, development 6 as support for the assessment, development 4 as support for the assessment, development 7 as counting against the assessment.
Its reason, as the model wrote it: Development 1 shows Alphabet signalling more AI spending after an $80.6 billion first-half outlay, supporting R1 and R2. Development 6 shows the AWS CEO publicly defending continued AI capital spending with a broad customer base, consistent with R2. Development 4 reports SOAR AI securing up to $1 billion in equity to fund AI infrastructure expansion, supporting R3. Development 7 notes some data-centre debt stress, which is a mild caution on R3, but it is a single source and does not indicate a broad spending reversal. The overall picture from the developments is that the largest spenders are sustaining and signalling further capital outlays through the relevant period.

The second round, after the check, which set the start

Reading 1: Likely (55–80%), from 7 developments shown. It relied on development 1 as support for the assessment, development 5 as support for the assessment, development 6 as support for the assessment, development 7 as counting against the assessment.
Its reason, as the model wrote it: Development 1 reports Alphabet signalling more AI spending after an $80.6 billion first-half outlay, supporting R1 and R2. Development 6 reports AWS CEO defending continued AI infrastructure spending, supporting R2. Development 5 notes Google Cloud surging at 82 percent and heavy spending starting to make sense, supporting R1 and R2. Development 7 raises some concern about data centre debt distress that could pressure financing, weakly bearing on R3, but the overall picture of rising hyperscaler commitments is strong.
Reading 2: Likely (55–80%), from 7 developments shown. It relied on development 1 as support for the assessment, development 6 as support for the assessment, development 5 as support for the assessment, development 7 as counting against the assessment.
Its reason, as the model wrote it: Development 1 (Alphabet signalling more AI spending after an $80.6 billion first-half outlay) directly supports R1 and R2, showing the largest cloud spenders continuing to raise capital expenditure. Development 6 (AWS CEO defending ongoing AI spending citing a broad customer base) supports R2. Development 5 (Google Cloud surging at 82 percent, making heavy spending look justified) supports R2 and reinforces that spending is not being cut. Development 7 (data centre debt distress noted) is a mild signal through R3 but does not dominate. Prior knowledge of publicly disclosed multi-year capex commitments by the hyperscalers set a high prior, and the developments support it.
Reading 3: Likely (55–80%), from 7 developments shown. It relied on development 1 as support for the assessment, development 6 as support for the assessment, development 10 as support for the assessment, development 7 as counting against the assessment.
Its reason, as the model wrote it: Development 1 reports Alphabet signalling continued heavy AI spending after an 80.6 billion dollar first-half outlay, directly supporting R1 and R2. Development 6 from the AWS CEO defends ongoing AI infrastructure spending with a broad customer base, also supporting R2. Development 10 addresses who is financing the data centre boom, supporting R3. Development 7 reports distress in some data centre debt markets, which is a mild signal against R3, though it covers specialized providers rather than the largest hyperscalers. On balance the evidence of continued and rising hyperscaler commitment is stronger than the single debt-distress report.
Reading 4: Likely (55–80%), from 7 developments shown. It relied on development 1 as support for the assessment, development 5 as support for the assessment, development 6 as support for the assessment, development 7 as counting against the assessment.
Its reason, as the model wrote it: Development 1 reports Alphabet signalling more AI spending after an $80.6 billion first-half outlay, supporting R2 by showing a raised spending outlook. Development 5 shows Google Cloud surging at 82 percent with heavy spending beginning to look justified, supporting R1 and R2. Development 6 shows AWS leadership defending ongoing AI infrastructure spending with a broad customer base, supporting R2. Development 7 flags some distress in data-centre debt markets, which could mildly count against R3, but the weight of evidence from the hyperscalers themselves points to continued rising capex, keeping the assessment likely.
Reading 5: Likely (55–80%), from 7 developments shown. It relied on development 1 as support for the assessment, development 6 as support for the assessment, development 7 as counting against the assessment.
Its reason, as the model wrote it: Development 1 (Alphabet signaling more AI spending after an $80.6 billion first-half outlay) supports continued growth in hyperscaler capital expenditure (factor R1 and R2). Development 6 (AWS CEO defending AI spending with a broad customer base) supports a sustained spending outlook (factor R2). Development 7 reports a Bloomberg Law piece on data center debt distress, which provides a mild caution on financing (factor R3), but this is a single source. The broader prior that the largest cloud companies have publicly committed to rising capital expenditure through 2026 and beyond remains intact, and no development shows a cut or pause in plans.

Readings made before this one

No starting point was read before this one, as the first day records.

Uncertainty

Causes of uncertainty

Quarterly spending is uneven and includes land, buildings and equipment that are not all for AI.
A growing share of AI capacity is financed off the largest companies' balance sheets, through leases and specialized providers, so their own spending can understate demand.
Outlooks are stated as ranges and revised each quarter, and a cut can reflect timing rather than intent.

What would change it

What would change the judgment

Combined quarterly spending by the four largest spenders falling below the same quarter a year earlier.
Two or more of them lowering their capital spending outlook in the same reporting season.
Leases signed but not yet started shrinking for two quarters running.

Causal factors

The causal factors, and which way each one cuts

Factor	Which way it cuts	What evidence looks like	Last moved
R1. Quarterly capital spending by the largest US cloud companies Payments for property and equipment by Microsoft, Alphabet, Amazon, Meta and Oracle, as filed with the SEC each quarter. Growth means demand keeps pressing on power. Public data that could later test this factor: quarterly payments for property and equipment by Microsoft, Alphabet, Amazon, Meta and Oracle, from their SEC filings. Not yet used as a test.	Supports. A stronger factor supports the assessment.	A 10-Q or 10-K showing year-over-year growth in payments for property and equipment. An earnings release reporting quarterly capital expenditure.	Not yet
R2. Capital spending outlook What those companies say they will spend in the current and next fiscal year, as stated in earnings releases and on earnings calls. A raised outlook means more pressure on power, and a cut means less.	Supports. A stronger factor supports the assessment.	An earnings release raises the full-year capital expenditure outlook. A company states that spending will rise again next year. A company lowers its outlook, which bears on the factor in the other direction.	Not yet
R3. Financing for data centre campuses Debt, lease and joint-venture financing for data centre campuses, including financing arranged outside the spenders' own balance sheets. Financing that closes on schedule keeps construction going.	Supports. A stronger factor supports the assessment.	A bond, loan or private-credit financing closes for a named campus. A joint venture is formed to fund a campus. A financing is withdrawn or repriced, which bears on the factor in the other direction.	Not yet
R4. Leases signed but not yet started Data centre leases that the largest spenders have signed but that have not yet commenced, as disclosed in the notes to their quarterly filings. These are contracted buildout, and growth means demand is committed ahead of supply.	Supports. A stronger factor supports the assessment.	A 10-Q or 10-K discloses a larger amount of leases not yet commenced. A company announces a long-term lease of a named campus.	Not yet
R5. Pauses, cancellations and lease exits Announced pauses, cancellations, deferrals or exits from leases by the largest spenders. More of these means demand presses less on power.	Weakens. A stronger factor weakens the assessment.	A company confirms that it has paused or cancelled a campus. A company is reported to have walked away from signed or negotiated leases.	Not yet

Assumptions

What the assessment assumes, and what would break it

RA1. The largest US cloud companies keep raising capital spending year over year through 2027.
If this fails, the assessment fails.
Invalidated if the combined quarterly payments for property and equipment of Microsoft, Alphabet, Amazon and Meta, 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), are lower than in the same calendar quarter a year earlier for two consecutive quarters.
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.
RA2. The largest spenders do not cut their spending outlooks together.
If this fails, the assessment weakens.
Invalidated if two or more of Microsoft, Alphabet, Amazon and Meta lower their stated capital expenditure outlook for the current or next fiscal year within the same quarterly reporting season, as stated in the earnings release furnished on Form 8-K or on the company's earnings call, excluding changes the company attributes to accounting or to how capital expenditure is defined. A lowered midpoint counts. A narrowed range does not.
Source: SEC EDGAR, Form 8-K earnings releases. The criterion’s fingerprint was fixed on 15 October 2026 and is part of the record’s first day.
RA3. Contracted data centre buildout keeps growing.
If this fails, the assessment weakens.
Invalidated if 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) fall at two or more of Microsoft, Alphabet, Amazon and Meta in each of two consecutive quarters.
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.

Other explanations

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.

RX1. Capital spending levels off in 2026 as the largest spenders absorb capacity already built.
No development was recorded on this assessment in the last 7 days.
Favoured by:
- Year-over-year growth in quarterly spending falls toward zero.
- Outlooks hold spending flat.
- Companies describe absorbing or digesting capacity already built.
Ruled out by:
- Quarterly spending is still growing year over year through 2027.
RX2. Spending moves off the largest companies' balance sheets to AI labs and specialized providers, so their own capital spending understates the demand on power.
No development was recorded on this assessment in the last 7 days.
Favoured by:
- AI labs sign large long-term capacity contracts with specialized providers.
- Campuses are financed through special-purpose vehicles.
- Spending is flat at the largest companies while contracted capacity elsewhere rises.
Ruled out by:
- Contracted capacity at specialized providers falls along with the largest companies' spending.

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

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.

Considered, set aside

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

Changes to this assessment

No change to this assessment yet.

The other assessments

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.