Does Coverage Acceleration Add Signal Beyond Velocity in Market-News Lifecycles?

Abstract Production market-news systems that cluster and rank stories rely on early coverage dynamics to decide which clusters will keep growing. A natural operational question is whether acceleration in unique-title arrivals — the curvature of coverage growth — carries forecasting information beyond the current level of coverage, its heat, and its recent velocity. We test this claim with a pre-registered, leakage-safe, cluster-level temporal study on 764 story clusters from a production deduplication and clustering system (81.6 days of as-of snapshot history, March–June 2026). At age six hours, we compare a regularized logistic baseline (levels, heat, title-arrival velocity, heat velocity, cadence) against an augmented model that adds a strictly backward-looking title-arrival acceleration proxy, for predicting at least two additional unique titles by age 18 hours. On the untouched chronological holdout (N=115, 30 positives), the acceleration proxy provides no improvement: ΔAP = −0.0121 absolute average-precision points (95% moving-block-bootstrap CI [−0.0536, +0.0125]), augmented log loss and ROC AUC are numerically worse, all four secondary randomization tests are non-significant (Holm-adjusted p = 1.0), and the pre-registered acceleration-permutation negative control fails: the observed ΔAP sits below the 95th percentile of its own permutation null (+0.0101). The primary hypothesis H1 is therefore classified NOTSUPPORTED under the frozen decision table. The level/heat/velocity baseline itself is strongly predictive of further cluster growth (AP ≈ 0.80, AUC ≈ 0.897), so the negative result is not a failure of the outcome to be learnable — it is a scoped falsification of the incremental acceleration claim. The outcome is coverage growth as recorded by the system, which includes late-ingested (backfilled) articles in 77/115 test clusters, including all 30 positives; the exclusion robustness (ΔAP = 0.0) is consistent with the null but underpowered (5 test positives). A null result of a valid execution is the deliverable; we do not reframe it. Hypotheses All hypotheses and the decision table were frozen on 2026-07-22 (with two logged pre-outcome amendments, see Analysis) before any predictor–outcome association, prediction, or performance metric was inspected. - H1 (primary) — moderate support expected, falsifiable. Among eligible clusters at age six hours, adding the preregistered backward-only acceleration proxy to the frozen baseline improves final chronological-holdout average precision for Y = 1[uniquetitlecount(18h) − uniquetitlecount(6h) ≥ 2]. Estimand: ΔAP = AP(augmented) − AP(baseline). Null: ΔAP ≤ 0. Material threshold: ΔAP ≥ 0.02 absolute AP points. - H2 (secondary) — moderate support expected. The augmented model has lower proper-scoring-rule loss (log loss) on the final holdout. Null: Δlogloss ≤ 0 (baseline minus augmented). - H3 (secondary) — moderate support expected. The augmented model has higher ROC AUC on the final holdout. - H4 (secondary family) — exploratory. Any primary-model advantage is directionally preserved under alternate labels Y = 1[Δuniquetitles ≥ 1] and ≥ 3. Decision rule for H1 (frozen): SUPPORTED only if ΔAP ≥ 0.02, the paired 95% moving-block-bootstrap lower bound 0, augmented test log loss is no worse than +0.01, and the observed ΔAP exceeds the 95th percentile of the acceleration-permutation null. Failure of the permutation control, or ΔAP ≤ 0, classifies H1 as NOTSUPPORTED (a null result remains release-eligible if the execution package is valid). Secondaries cannot rescue H1 and are Holm-corrected across the four p-values at family-wise α = 0.05. Data Provenance The data source for every analysis in this paper is a canonical immutable JSONL extract of the exact 764-cluster cohort, frozen on 2026-08-05 and stored as protocol/input-extract.jsonl (1,634,426 bytes, SHA-256 103c46c8…), whose canonical-cohort SHA-256 (f47d0dfb…) matches the frozen split counts. The analysis verifies both hashes before reading any feature or outcome value; a mismatch invalidates the experiment. The extract derives from the PerpsTrader production news database (/home/d/PerpsTrader/data/news.db, 125,662 newsarticles, 11,445 storyclusters, 13.5M clusterheathistory rows) — real production system records, not simulated. The SCOUT snapshot's physical database hash could not be reproduced later because the live append-only database had drifted, so the freeze amendment made the extract the sole experiment input. Data provenance is therefore REAL production records via frozen immutable extract (reliability of the records as database entries: RELIABLE after hash verification; as measurements of external ground truth: not error-free). | Input or output | Provenance | Reliability | Appropriate interpretation | |---|---|---|---| | 764-cluster JSONL extract | Frozen 2026-08-05, hash-verified | RELIABLE as the exact experiment input | Sole data for all results | | Stored heat/count/velocity fields | As-of da