Biophysical Reviews: from the umbra of 2020–2021 into the antumbra of 2022
Bibliographic record
Abstract
This sub-Editorial for Volume 14 Issue 1 (2022) first makes comment on the current issue and then describes matters of interest related to the journal's activities in 2022-chief among which are (i.) the announcement of the winner of the 2022 Michèle Auger Award for Young Scientists' Independent Research, (ii.) an outline of this year's finalized Special Issue (SI) lineup, (iii.) a description of a new production service offered by Springer to those submitting to the Biophysical Reviews journal, and (iv.) an introduction of newly appointed members of the Biophysical Reviews' Editorial Board.
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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 | 0.011 | 0.027 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.007 | 0.013 |
| Insufficient payload (model declined to judge) | 0.031 | 0.030 |
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".