Abstract 5319: The role of ISBER (The International Society for Biological and Environmental Repositories) in cancer research
Bibliographic record
Abstract
Abstract High quality biospecimen collections are essential for biomarker discovery in Cancer Research. Biomarker analytical and clinical performance depends heavily upon the pre-analytical variation of biospecimens used. For this reason, standardization of procedures is of utmost importancein the collection, preparation, and storageof biospecimens, making it possible to accurately associateprocessing methods withappropriate end-use applications. The International Society for Biological and Environmental Repositories (ISBER) is a professional society of organizations and individuals who share an interest in promoting consistent, high quality standards, ethical principles, and Best Practices in biospecimen banking. ISBER, with almost 500 individual and organizational members throughout the world, is the leading international forum for promoting innovation in the science and management of biospecimen collection, processing, storage, distribution, and use. ISBER educational resources and meetings focus on a wide variety of topics from biorepository development, maintenance, and improvement, to technical concerns regarding equipment, quality assurance and control, regulation, human subject privacy, and confidentiality. Additional tools developed by ISBER, many of which are web-based, are available to assist researchers in ensuring biospecimen quality and biorepository compliance with Best Practices. ISBER routinely provides information about existing biorepositories and their biospecimen collections as well. For more information, please visit http://www.ISBER.org. Citation Format: Debra L. Garcia, Katherine Sexton, William E. Grizzle, Fay Betsou. The role of ISBER (The International Society for Biological and Environmental Repositories) in cancer research. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 5319. doi:10.1158/1538-7445.AM2014-5319
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.126 | 0.125 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.025 | 0.017 |
| Open science | 0.006 | 0.018 |
| Research integrity | 0.010 | 0.006 |
| Insufficient payload (model declined to judge) | 0.103 | 0.056 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".