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Market Trust Card v0.1polymarket24h public snapshot

what-price-will-bitcoin-hit-before-2027

Will Bitcoin reach $100,000 by December 31, 2026?

This market may be useful as an input, but it carries visible quality caveats. Cite the probability only alongside those caveats.

Use with caveats
73/100

Measured-only score

71/100 from 3 measured pillars

The measured pillars and the heuristic mix agree within 5 points; the rating does not lean on heuristic priors.

Measured weight share 51%

Rating is about whether this market is currently citable as evidence, not whether the outcome will resolve yes or no.

Evidence coverage

Partial v0.1 coverage

3 measured · 3 heuristic · 1 pending pillar

Mid price

48.5%

Spread

1.00%

Liquidity

$115k

Visible depth

$177k

Modeled depth at size

$3k

Resolution risk

14.0%

Evidence status

The v0.1 score is only as strong as the measured inputs behind it. This breakdown keeps placeholder pillars from looking as firm as source-backed metrics.

Measured

3

Directly derived from current source artifacts, such as market metadata, orderbook snapshots, or Coherence Signal context.

Heuristic

3

Computed from frozen v0.1 rules, but not yet validated against a resolved scorecard cohort.

Pending

1

Reserved for inputs Convexly has not joined into this market-level artifact yet.

Score waterfall

The composite reweights only scored pillars. Pending inputs are visible, but they contribute zero points until the evidence is joined.

Rounded composite

73

Coherence

raw weight 20.0%

normalized 22.7%

30 x 22.7% = 6.8 pts

Liquidity

raw weight 16.0%

normalized 18.2%

98 x 18.2% = 17.8 pts

Orderbook depth

raw weight 15.0%

normalized 17.0%

97 x 17.0% = 16.5 pts

Modeled depth at size

raw weight 13.0%

normalized 14.8%

61 x 14.8% = 9.0 pts

Participant quality

raw weight 12.0%

normalized 0.0%

unscored

Manipulation risk

raw weight 12.0%

normalized 13.6%

78 x 13.6% = 10.6 pts

Resolution reliability

raw weight 12.0%

normalized 13.6%

86 x 13.6% = 11.7 pts

Unrounded contribution total 72.55 · displayed score rounds to 73

Pillar readings

Coherence

Measured

A same-event CME constraint fired near this market; the score discounts larger tensions.

30
/100
  • Matched MENE cluster with 26.9pp raw tension and z=36.0.
  • This is a structural-coherence reading, not a forecast of the market outcome.

Source refs

gamma_snapshot.json:0xdaa4866bae18be58c5a79d2aeeffd035ec78f1bb49dbd88f72993997778a990f

orderbook_snapshots.jsonl:0xdaa4866bae18be58c5a79d2aeeffd035ec78f1bb49dbd88f72993997778a990f

cme_signal_report_full.json:matched_cluster

Liquidity

Measured

Log-scaled liquidity and historical volume from the Gamma market snapshot.

98
/100
  • Liquidity is $115k and historical volume is $1.5m.
  • The score is log-scaled so a market must be meaningfully liquid, not merely nonzero.

Source refs

gamma_snapshot.json:0xdaa4866bae18be58c5a79d2aeeffd035ec78f1bb49dbd88f72993997778a990f

orderbook_snapshots.jsonl:0xdaa4866bae18be58c5a79d2aeeffd035ec78f1bb49dbd88f72993997778a990f

Orderbook depth

Measured

Top-of-book plus full-ladder depth, penalized for wide spreads.

97
/100
  • Full visible ladder depth is $177k; top-of-book depth is $604.
  • Yes-side bid/ask spread is 1.00pp.

Source refs

gamma_snapshot.json:0xdaa4866bae18be58c5a79d2aeeffd035ec78f1bb49dbd88f72993997778a990f

orderbook_snapshots.jsonl:0xdaa4866bae18be58c5a79d2aeeffd035ec78f1bb49dbd88f72993997778a990f

Modeled depth at size

Heuristic

Heuristic depth-at-size band from visible CLOB depth and gamma liquidity proxies. v0.1 does not measure executable fill against a real-size trade and the score is not a tradable capacity claim.

Modeled estimate · not a per-market measurement

~61
modeled
  • Modeled depth band at size is $3k based on visible CLOB depth and the gamma liquidity proxy.
  • vwap_fill_against_ladder is not yet wired into per-card output; the band is heuristic, not measured executable fill.
  • The card intentionally does not expose trade direction or executable trade construction.

Source refs

gamma_snapshot.json:0xdaa4866bae18be58c5a79d2aeeffd035ec78f1bb49dbd88f72993997778a990f

orderbook_snapshots.jsonl:0xdaa4866bae18be58c5a79d2aeeffd035ec78f1bb49dbd88f72993997778a990f

Participant quality

Pending

Market-level wallet rollups are not yet joined in v0.1.

—
unscored
  • Wallet skill exists at the leaderboard/analyzer layer, but per-market participant joins are still pending.
  • This pillar is deliberately unscored so the composite does not imply informed-flow evidence we do not have yet.

Source refs

wallet_activity_snapshots:parser_pending

Manipulation risk

Heuristic

Heuristic only: v0.1 reads structural risk indicators (spread, volume, depth) and does not look at per-market wash trading or insider flow. A high score does not mean the market is measured manipulation-free; it means the structural indicators are not flagging.

Modeled estimate · not a per-market measurement

~78
modeled
  • v0.1 flags shallow or wide markets as easier to move, but does not claim to detect coordinated manipulation.
  • No per-market wash-cluster or insider-detector evidence is joined into v0.1; that input ships with the v0.2 manipulation rollup.
  • Future versions should incorporate wallet-cluster graphs, wash flags, and flow concentration.

Source refs

gamma_snapshot.json:0xdaa4866bae18be58c5a79d2aeeffd035ec78f1bb49dbd88f72993997778a990f

orderbook_snapshots.jsonl:0xdaa4866bae18be58c5a79d2aeeffd035ec78f1bb49dbd88f72993997778a990f

Resolution reliability

Heuristic

Heuristic v0.1 inversion of the CME resolution-risk score. Inputs are subjective wording, liquidity floor, time-to-resolution, and category keyword priors. The score is not calibrated against historical UMA dispute rates yet, so a high reading means the heuristic flags are absent, not that resolution has been measured reliable.

Modeled estimate · not a per-market measurement

~86
modeled
  • Max resolution risk input is 0.140.
  • Thresholds are MVP heuristics and must be re-audited before v0.2 validation claims.

Source refs

services/api/scripts/cme_v0_1/resolution_risk.py

gamma_snapshot.json:0xdaa4866bae18be58c5a79d2aeeffd035ec78f1bb49dbd88f72993997778a990f

orderbook_snapshots.jsonl:0xdaa4866bae18be58c5a79d2aeeffd035ec78f1bb49dbd88f72993997778a990f