Methodology
The current V4 baseline, the pre-registered V5 research target, acceptance gates, platform support, uncertainty, and limitations.
Frozen v4 traction baseline
The score currently visible in the graph is the immutable v4 deterministic index and rollback baseline. It is not a calibrated probability, a causal estimate, or a learned prediction of company quality. V5 will replace it only after compatible longitudinal data, leakage-safe held-out evaluation, calibration, reproducibility, subgroup, and runtime-parity gates all pass.
V5 validated platform coverage is currently none: every platform remains v4-only until it has enough compatible, licensed, longitudinal examples to clear the same held-out acceptance gate. An unsupported V5 row is unscored rather than routed through another platform's parameters.
This is a historical-score interpreter for returner-traction v4.0.0, not the intended learned V5 formula. V4 starts with verified native evidence whose configured visible metrics are normalized to canonical aliases. It multiplies each raw count by the table value, applies a platform-specific logarithmic reference, and blends 85% absolute signal with 15% within-platform midrank.
Evidence then blends 75% durable signal with 25% recency momentum. A missing publication date uses the historical momentum value 0.45. Duplicate physical posts count once; only the strongest 5 posts per platform contribute, at 82%, 8%, 5%, 3%, 2% by slot. Posts are therefore not simply summed without limit.
Platform results use the configured platform shares below; breadth is not a separate bonus in this V4 configuration (0% strongest-platform blend and 100% configured diversified blend). Company calibration blends 82% absolute score with 18% tie-aware cohort percentile, then stretches the positive company cohort across the 1–100 range (companies without eligible evidence remain 0). Filters only change visibility and never recompute this canonical result.
| Platform | Share | Log reference | Half-life | Raw metric weights before normalization |
|---|---|---|---|---|
| GitHub | 15% | 40,000 | 365 days | stars × 1.5 · forks × 4 · recent_commits_30d × 1 · issues × 0.5 |
| X | 21% | 120,000 | 45 days | views × 0.04 · likes × 1.4 · replies × 4.5 · reposts × 6 · quotes × 6 |
| 15% | 18,000 | 75 days | views × 0.04 · reactions × 1.4 · comments × 4.5 · reposts × 6 | |
| 21% | 80,000 | 60 days | views × 0.04 · likes × 1.1 · comments × 4.5 · shares × 5 · saves × 4 | |
| Product Hunt | 7% | 4,000 | 120 days | upvotes × 2 · comments × 3.5 |
| YouTube | 10% | 35,000 | 150 days | views × 0.025 · likes × 1 · comments × 3.5 |
| 4% | 4,000 | 60 days | upvotes × 2 · comments × 3.5 | |
| Hacker News | 5% | 2,500 | 60 days | upvotes × 2 · comments × 3.5 |
| Bilibili | 2% | 35,000 | 150 days | views × 0.025 · likes × 1 · comments × 3.5 · shares × 4 |
V4 confidence is separate from score: its heuristic starts at 20%, then uses evidence depth (38%, scale 4), platform breadth (22%), publication-date coverage ( 12%), and verified links (8%). Medium/high labels begin at 50%/75%. These weights, references, half-lives, slot shares, missing-date behavior, and calibration blend are product heuristics preserved only for V4 history and rollback; they are not fitted V5 parameters.
V4 summarizes verified, visible platform-native traction evidence on a bounded 0–100 index. The proposed V5 target is a pre-registered future platform-native performance outcome observed after a genuine t0 measurement; it will be labeled as a probability or percentile only if held-out calibration supports that interpretation.
The versioned source registry separates incorporated, rejected, unavailable, and license-restricted benchmarks. Citation alone does not count as incorporation: data, protocol, baseline, failure-mode test, or acceptance gate must actually enter the reproducible pipeline.
The pre-registered design keeps canonical physical posts in one split, places training before validation and validation before final test, and reserves an entity holdout for future unseen-company evaluation. Planned leave-one-batch-out checks are separate development analyses. The current rejected artifact has no rows, so it reports no unseen-company or unseen-batch result and the final test has not selected a model.
V5 candidates use only features genuinely available at the observation timestamp, including missingness and post age. Separate native signals are not collapsed with a hand-selected exchange rate. Monotonic candidates ensure that increasing a genuine positive signal cannot lower a prediction. Signal-family ablations remain a held-out acceptance requirement; none is reported for the current zero-row rejected artifact.
No hand-picked multiplier or top-post slot vector is accepted for V5. Linear coefficients, spline effects, calibration maps, temporal curves, and company pooling parameters must be fitted under the frozen search protocol and survive held-out evaluation. Nonlinear marginal effects depend on platform, age, and context.
V5 does not assume that platform breadth is beneficial. Cross-platform combination must be learned and validated, or platform scores remain separate. Coverage may narrow uncertainty without secretly adding score points. Visibility filters never recompute a canonical score.
Any promoted output will document its bounds and exact semantics. A future frozen search may compare recency-free and learned age-effect candidates, but the current rejected artifact fitted no temporal curve. No manually chosen half-life or guessed missing-date prior is permitted. Unknown publication dates remain unscored unless a separately validated path exists.
Score, predictive uncertainty, evidence coverage, link verification, date quality, and source reliability are separate fields. A completeness heuristic is never called a statistical interval. Unsupported platforms and out-of-distribution inputs remain visibly unscored.
Public engagement is selected, platform-dependent, missing-not-at-random, and potentially manipulated. The model does not establish causality, company quality, valuation, or investment outcomes. Fairness and transfer claims are limited to the subgroups and platforms actually tested.
Lines explain only the relationship types present in the map, such as shared industry context or a shared group partner. They do not imply company interaction and never add score points. The map legend exposes the exact relationship explanations available in this graph.
A future accepted V5 artifact will state: “The parameters were fitted on versioned benchmark and longitudinal data under a frozen evaluation protocol. They are predictive associations for the stated target, not causal estimates of company quality or investment outcomes.” Until that gate passes, the product makes no such fitted model claim.
Read the visible model version before comparing scores, and use the native evidence, observation cutoff, coverage, and limitations alongside the number. See data sources for provenance and corrections for disputed records.