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[submitted] SDSS/BOSS-RCA

SDSS/BOSS-RCA is a Python command-line and guided-menu tool for post-pipeline residual-covariance advisory analysis of selected SDSS/BOSS spectral samples. It builds auditable RCA matrices from SDSS/BOSS DR12 spec-lite or plate-MJD-fiber selections, applies conservative mask/inverse-variance handling, computes residual-correlation diagnostics, evaluates alignment-sensitive diagnostic controls, and produces conservative advisor decisions focused on naive stacking, averaging, independence, and uncertainty assumptions.

The software automates the end-to-end diagnostic workflow, from selected-spectrum ingestion and RCA matrix construction to residual-correlation diagnostics, diagnostic controls, advisor decisions, report generation, and traceability packaging. It generates author- and reviewer-facing PDF reports, visual diagnostic summaries, JSON manifests, SHA-256 fingerprints, QR/fingerprint verification blocks, and reproducible audit artifacts, reducing the manual time required to assemble, document, and review residual-covariance evidence for a selected SDSS/BOSS spectral matrix.
SDSS/BOSS-RCA belongs to the broader FRANJAMAR-RCA ecosystem of post-pipeline residual-covariance advisor tools. Within this ecosystem, several survey- and mission-specific RCA branches share a common diagnostic philosophy, partially aligned RCA command-line grammar, guided-menu design, traceability model, report-generation approach, and reviewer-facing interpretation boundary, while each branch retains its own data-ingestion layer, adapters, validation examples, and instrument- or survey-specific limits.

SDSS/BOSS-RCA does not replace the official SDSS/BOSS pipeline, recalibrate spectra, validate redshifts, certify data quality, or validate physical or cosmological conclusions. Its purpose is to make residual-covariance assumptions visible, reproducible, auditable, and easier to inspect for selected SDSS/BOSS spectral matrices.

Code site:
https://doi.org/10.5281/zenodo.20832322
Preferred citation method:

Please cite the Zenodo software DOI: 10.5281/zenodo.20832322


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