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Record W4413108961 · doi:10.1177/19475535251365758

The College of American Pathologists Biorepository Accreditation Program: Results from the First 10 Years

2025· article· en· W4413108961 on OpenAlexaff
Nalin Leelatian, Joan Rose, Richard Davis, Helena Ellis, Di Jing, Basal Kashlan, Nilsa C. Ramirez, Jim Vaught, Erik Zmuda, Shannon J. McCall, Rebecca C. Obeng

Bibliographic record

VenueBiopreservation and Biobanking · 2025
Typearticle
Languageen
FieldMedicine
TopicClinical Laboratory Practices and Quality Control
Canadian institutionsEngineers Without Borders Canada
Fundersnot available
KeywordsBiorepositoryAccreditationMedical educationMedicineBiologyBioinformaticsBiobank

Abstract

fetched live from OpenAlex

INTRODUCTION: The College of American Pathologists (CAP) Biorepository Accreditation Program (BAP) was established in 2012 with the goal of providing standardized requirements that ensure high quality for procuring, processing, storing, distributing, and computerizing information of biospecimens for scientific investigations. CAP BAP was the first biorepository accreditation program, and, since the program started in 2012, the world's second biorepository accreditation standard was issued by the International Organization for Standardization (ISO) as ISO 20387 in 2018. CAP BAP serves as an interface between several programs and draws best practices from renowned organizations. This elective program is based on a peer-inspection model to ensure that the inspectors have proper expertise and to promote educational efforts through information sharing. On-site inspections occur every 2 years, like other CAP Accreditation Programs, with an interim self-inspection in the off year. The program compliance is assessed based on CAP Accreditation Checklists, which are regularly revised. OBJECTIVE: This article reviews the accomplishments of the first 10 years of the CAP Biorepository Accreditation Program. RESULTS: As of December 2024, 104 biorepositories are CAP BAP accredited, which increased from 53 accredited biorepositories in 2018. Accreditation of 10 additional biorepositories is underway. A total of 88 inspections were completed between January 2017 and December 2022; 16 were initial inspections and 72 were reinspections. Deficiencies, defined as insufficient or lack of evidence of compliance with a checklist item, were mainly related to equipment/instrumentation (24%), quality management (15%), safety (14%), information technology (13%), personnel (13%), specimen handling and quality control (9%), facilities (6%), and regulatory (6%) issues. The proportion of deficiencies between categories was like the first 5 years. CONCLUSION: The increased number of accredited biorepositories, in both academic and commercial settings, highlights the continued success of the program and its applicability to maintaining high standards for biorepositories.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.030
metaresearch head score (Gemma)0.061
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.970
Threshold uncertainty score0.160

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0300.061
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.007
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0020.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.045
GPT teacher head0.362
Teacher spread0.317 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designObservational
DomainEvaluation
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes1
Has abstractyes

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