Why KELLY can be stronger here
KELLY is designed to win by being scoreable: every forecast should connect to source evidence, causal assumptions, falsifiers, settlement, calibration, replay, and memory lineage.
why it mattersA forecast platform is only as good as its ability to be wrong in public, adjust from reality, and improve the next forecast without hiding the chain.
sector edgeShows research metadata, citation trails, claim uncertainty, and source provenance.
best claim boundaryKELLY should be called better only where its scorecards, calibration, replay receipts, and source coverage outperform alternatives. This page is built to make that measurable.
Where the proof lives
proofSource plan: the approved feed rows on this page
proofForecast method: the doctrine timeline on this page
proofAuthority evidence: Authority Index and replay receipts
proofScore evidence: settlement and calibration records
proofSystem evidence: Brain Fleet, generality evidence, and advanced proof labs
Professional layout pattern
The lab layout follows successful product patterns: fast first read, watchable objects, citations beside claims, source freshness, score history, and direct proof links.
patternCitation-forward answer pattern: put sources and proof next to claims.
patternForecasting track-record pattern: keep probability, resolution rule, score, and history together.
patternWatchlist pattern: let users inspect a saved set without writing ground truth.
patternAlert/status pattern: show what changed, what is stale, and what KELLY is watching.
Research references
TradingViewCharts, alerts, screeners, replay, multi-chart layouts, and fast command/search patterns make market work feel immediate. MetaculusForecast questions need clear resolution rules, track records, scoring, calibration, and aggregation history. Windy / Windy.appWeather users need maps, layers, local points, alerts, history, model comparison, and fast location context. PerplexityAnswer users expect citations beside claims, follow-up context, and checkable source trails.
KELLY's specialized forecast method
Shows research metadata, citation trails, claim uncertainty, and source provenance. KELLY routes this through tagged intake, causal pressure nodes, forecast lanes, settlement, calibration, and replayable memory evidence.
1Approved source intake only
2Tag source, freshness, domain, and authority
3The Book of Why: ask what caused the change, what would have happened otherwise, and what evidence can falsify the causal story
4Thinking in Systems: map feedback loops, delays, stocks, flows, constraints, and downstream effects
5Thinking, Fast and Slow: separate fast pattern recognition from slower deliberate verification
6Superforecasting: start with base rates, update incrementally, keep probabilities explicit, and score the forecast later
7Thinking in Bets: treat every forecast as a wager against reality with a clear settlement rule
8Build causal pressure nodes and forecast cones
9Separate KELLY forecast from user forecast
10Track falsifiers, uncertainty, and competing explanations
11Close against reality
12Score calibration and error direction
13Apply continuous micro-adjustments after settlement to improve future accuracy
14Create replayable memory evidence when eligible
What this lab is for
Showing KELLY using papers, metadata, and citations as evidence that still needs reality closure.
safe claimShows research metadata, citation trails, claim uncertainty, and source provenance.
boundaryNo medical, scientific, or safety conclusion without domain review and evidence closure.
Live proof status
proof score50 / early
visible cells0
readiness score0%
sources wired3/3
public writesblocked
Proof links
Every useful view should expose source provenance, causal node, settlement rule, calibration result, and replay/memory eligibility when available.
Approved source plan
| source | status | cost | role |
|---|
Crossref
crossref |
wired |
free_no_key |
Publication metadata and DOI records. |
arXiv
arxiv |
wired |
free_no_key |
Preprint metadata and research trend signals. |
Wikimedia Analytics
wikimedia-aqs |
wired |
free_no_key |
Public attention and pageview context. |
User questions this lab can inspect
| question lane | plain question | node |
|---|
| Claim strength |
How strong is this claim? |
SCIENCE:CLAIM_STRENGTH |
| Replication risk |
What could fail to replicate? |
SCIENCE:REPLICATION_RISK |
| Attention shift |
Is attention changing? |
SCIENCE:ATTENTION_SHIFT |
| Source quality |
Can KELLY trust this source? |
SCIENCE:SOURCE_QUALITY |
Default focuses
| focus | meaning | context |
|---|
| Crossref |
published metadata |
|
| arXiv |
preprint signal |
|
| Wikimedia AQS |
public attention signal |
|
| Open scholarly graph |
knowledge graph context |
|
Causal pressure map
SCIENCE:SOURCESCIENCE:CITATION_CONTEXTSCIENCE:CLAIMSCIENCE:FALSIFIERSCIENCE:MEMORY_ELIGIBLE
causal linkSCIENCE:SOURCE -> SCIENCE:CLAIM
causal linkSCIENCE:FALSIFIER -> SCIENCE:CLAIM
causal linkSCIENCE:CLAIM -> SCIENCE:MEMORY_ELIGIBLE
Boundary receipt
{
"readOnly": true,
"publicUserWriteAllowed": false,
"noAdviceSubstitute": "No medical, scientific, or safety conclusion without domain review and evidence closure.",
"noClaimOfPerfectPrediction": true,
"proofRequiredForEveryForecast": true
}