Catalog, code, and supplementary data for: A selection-corrected framework for warm extreme debris incidence in nearby FGKM dwarfs

Catalog products, analysis code, and supplementary tables and figures supporting the paper "A selection-corrected framework for warm extreme debris incidence in nearby FGKM dwarfs: pre-main-sequence contamination of the Scorpius-Centaurus signal and the limits of AllWISE depth" (Greenberg 2026). This deposit provides the complete data, code, and supplementary materials required to reproduce the analysis presented in the paper, which develops a selection-corrected framework for warm extreme debris disk (EDD) incidence rates around nearby FGKM dwarfs at fractional luminosities L_dust/L_star greater than or equal to 0.01. The framework comprises three principal components: (i) a seven-mechanism contamination vetting cascade applied to AllWISE infrared excess candidates within 200 parsecs, (ii) a per-star Monte Carlo detection efficiency calculation incorporating the AllWISE survey-depth fallback noise model for stars without confident W4 detection, and (iii) a BANYAN Sigma kinematic membership decomposition separating field-star from young-moving-group affiliates. Applied to 136,553 Gaia DR3 plus AllWISE plus 2MASS FGKM dwarfs within 200 pc, the framework identifies that approximately 60 percent of the apparent six-mechanism M-dwarf elevation over FGK, and substantially all of the apparent Scorpius-Centaurus warm-debris enrichment in the solar neighborhood, is contamination by pre-main-sequence circumstellar disks. Mechanism 7, a NEOWISE-R W1+W2 variability vetting layer with W1-W2 SED-shape diagnostics, identifies and removes this population. After variability vetting and symmetric BANYAN kinematic field-cleaning, the field-cleaned M-dwarf elevation at L_dust/L_star greater than or equal to 0.01 is E(0.01) = 2.19 with 68 percent Feldman-Cousins confidence interval [1.05, 4.57], marginally above unity at 68 percent confidence but consistent with unity at 95 percent confidence and not statistically robust. Deposit contents include: Catalog products: extreme_debris_catalog.parquet and extreme_debris_catalog.csv (the 64-entry post-vetting candidate catalog with 53 columns of SED fitting and quality flags), pass_list_final_v2.csv (pass/fail decisions per entry across all seven mechanisms with BANYAN classifications), fgk_numerator_targets.csv and m_dwarf_numerator_targets.csv (the 17 FGK and 23 M-dwarf numerator entries respectively). Analysis code: extreme_debris_catalog.py (catalog construction), detection_efficiency_mc.py and run_efficiency_extended.py (per-star Monte Carlo efficiency calculation), neowise_variability.py (mechanism 7 NEOWISE-R variability classification), compute_post_variability_rates.py (rate computation pipeline), lockdown_checks.py (independent cross-checks), diagnose_insufficient.py and diagnose_insufficient_fgk.py (manual reclassification of insufficient_data entries). Mechanism 7 outputs: neowise_variability_per_target_M.csv and _FGK.csv (per-target Stetson J statistic and classification), neowise_variability_per_epoch_M.parquet and _FGK.parquet (per-epoch NEOWISE-R lightcurve data), outputs_relaxed.tar.gz and outputs_fgk_relaxed.tar.gz (consolidated per-target classification outputs). Detection efficiency outputs: efficiency_per_star.csv (production L_dust/L_star greater than or equal to 0.01 case) and efficiency_per_star_L0_02.csv, L0_03.csv, L0_05.csv (threshold-robustness variants). Rate computation outputs: post_variability_rates.csv, post_variability_elevation.csv, rate_computation_field_cleaned_N8.csv, rate_computation_conservative_N7.csv, rate_computation_symmetric_field_cleaned.csv (the three principal rate scenarios reported in the paper). BANYAN membership: banyan_membership_all_40.md (BANYAN Sigma posteriors and subgroup affiliations for all 40 numerator entries). Validation and supplementary diagnostics: lockdown cross-checks against ASAS-SN and Gaia DR3 variability, Stetson J null distribution, sky position visualization, catalog audit, photometry artifact checks, GALEX UV cross-match diagnostics, far-IR candidate notes, pipeline patch report, rate calculation supplement, sensitivity tests for k_recover and fallback depth, efficiency versus dust temperature extended diagnostics, and variability vetting supplement. A complete README.md is included in the deposit, mapping all files to manuscript sections and providing reproduction instructions.