Bibliographic record
Abstract
A few years ago Journal of Biocommunication found itself in a unique position. The JBC Board faced challenges relating to new publishing demands from the National Institutes of Health, state-supported universities, Canadian universities, and non-profit reserach institutes. The JBC needed to embrace these new open access rquirements, yet felt that it should maintain a fully copyrighted environment for illustrators, photographers, and others who wanted that traditional protection. The JBC's solution was to publish in a dual environment withing a Open Journal Systems framework. We rely on our readership for feedback about the Journal, and we invite you to share your thoughts with us about any of our columns and articles. We always appreciate your suggestions for improvement. JBCeditor@ami.org
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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 | 0.007 | 0.067 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.007 | 0.004 |
| Research integrity | 0.058 | 0.047 |
| Insufficient payload (model declined to judge) | 0.082 | 0.115 |
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".