Updating International Society for Biological and Environmental Repositories Best Practices, Fifth Edition: A New Process for Relevance in an Evolving Landscape
Bibliographic record
Abstract
The recently published fifth edition of the International Society for Biological and Environmental Repositories (ISBER) Best Practices signifies a pivotal milestone in navigating the complexities of repository management. Repositories operate within a constantly evolving landscape influenced by the changing fields of biospecimen science, technology, legal requirements, and ethical considerations. This dynamic is further amplified by unprecedented local and global challenges, such as pandemics, conflicts, and supply chain disruptions. Creating this new edition required a comprehensive approach capable of delivering a focused and coherent resource reflecting the broad horizon of its diverse users. The innovative approach used the existing phased development process and integrated the canvassing of opinions, formal evaluation, and real-time collaboration platforms. Merging these techniques enabled efficient collection and effective distillation of the latest in biobanking practices, enhancing the value of the fifth edition for repositories of specimens and associated data. The expanded document is a testament to the collective efforts of many dedicated individuals who have built upon the foundations of prior editions.
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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 | 0.097 | 0.230 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.013 | 0.010 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.037 | 0.021 |
| Open science | 0.005 | 0.016 |
| Research integrity | 0.010 | 0.016 |
| Insufficient payload (model declined to judge) | 0.010 | 0.012 |
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".