SETAC GLB and SETAC Europe SAC: a liaison promoting the next generation of ecotoxicologists and environmental chemists
Bibliographic record
Abstract
This commentary is an introduction for students to the Society of Environmental Toxicology and Chemistry (SETAC) and its Student Advisory Council (SAC). As young academics face challenges while trying to develop their careers, SETAC and the SAC help facilitate student involvement in the various communities within the society that can help to develop the students' careers within the environmental sciences [e.g. the German Language Branch (GLB)]. This piece would also like to emphasize and pay homage to the continual cooperation between the SAC and the ESEU, which provides a scientific platform to communicate internationally and beyond the borders of SETAC, as well as offer heartfelt congratulations from the SAC to the GLB for their "20 Years SETAC GLB" and deep gratitude for their strong advocacy and support of the SAC.
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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 | 0.012 | 0.029 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.025 | 0.030 |
| Insufficient payload (model declined to judge) | 0.015 | 0.013 |
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".