LIFECYCLE-SEPARATION-2026-v1: Sniper Cohort and Algorithmic Rejection Datasets for Two-Window Lifecycle-Stage Separation Analysis in Solana Memecoin Markets

LIFECYCLE-SEPARATION-2026-v1 is a reproducibility bundle for the paper "Sniper Cohorts and Algorithmic Filter Rejections in Solana Memecoin Markets: Two-Window Replication of Lifecycle-Stage Population Separation" (Kamat, 2026). The bundle contains three data files, eight analysis-output reports, seven analysis scripts, LICENSE, README, SCHEMA, and SHA256SUMS. The datasets support the empirical claim that two independent algorithmic detection streams applied to the same Solana memecoin market during the same observation windows produce nearly disjoint token-set outputs. In the June 2026 window, 2 of 20,162 sniper-cohort-detected mints (0.010 percent) appear in the algorithmic rejection stream. In the July 2026 window, 5 of 623 cohort-detected mints (0.803 percent) appear. Cross-window cohort overlap between v1 and v2 is zero mints. The finding replicates in order of magnitude across pipeline versions and time windows despite substantial variation in detector selectivity and rejection-stream coverage. The separation is structural: cohort detection operates at the pump.fun bonding-curve stage, while rejection filtering operates on PumpSwap and other post-graduation venues. Four alternative explanations (time-window artifact, data-source mismatch, DEX venue asymmetry, pipeline-version artifact) are systematically ruled out. Contents: sniper_cohorts_intra_v2.jsonl (428 KB, 623 rows) — v2 cohort detections, June 29 to July 16, 2026 UTC; rejection_outcomes_v1_window.jsonl.gz (1.2 MB, 12,688 rows) — post-rejection outcome samples in the v1 cohort window; rejection_outcomes_v2_window.jsonl.gz (30 MB, 238,722 rows) — post-rejection outcome samples in the v2 cohort window; analysis_outputs/ — 8 text and CSV reports; scripts/ — 7 Python 3 analysis scripts; LICENSE, README.md, SCHEMA.md, SHA256SUMS. The v1 cohort dataset (sniper_cohorts_intra.jsonl, 20,162 mints) referenced in the paper is not included here because it is already publicly available as part of RED-COHORT-2026-v1 on Zenodo (concept DOI 10.5281/zenodo.20978741). All numbers reported in the paper reproduce byte-for-byte from the data files using the included scripts. Total runtime under 5 minutes on a modest single-vCPU machine. Patent and commercial licensing disclosure: The dataset itself is released under CC-BY-4.0. The author holds pending USPTO Provisional Patent Applications in the field of algorithmic decentralized-exchange trading and blockchain market microstructure, including UDAY P1 #64/022,461 (filed 2026-03-30, Micro Entity) and UDAY P2 #64/099,108 (filed 2026-06-25, Micro Entity). The release of this dataset under CC-BY-4.0 does not affect patent priority claims under 35 USC 102(b)(1)(A). Commercial re-implementation of specific methodologies covered by pending patent claims may require patent licensing. Academic re-implementation is unaffected. Ethics: All data are public Solana base-58 addresses. No personally identifying information is included. Suggested citation: Kamat, A. U. (2026). LIFECYCLE-SEPARATION-2026-v1: Sniper Cohort and Algorithmic Rejection Datasets for Two-Window Lifecycle-Stage Separation Analysis in Solana Memecoin Markets [Data set]. Zenodo. For commercial licensing inquiries: [e-mail]