Comparison between activity estimates obtained using bioenergetic and behavioural analysesContribution of the Groupe de Recherche Interuniversitaire en Limnologie (GRIL).
Bibliographic record
Abstract
Activity rate of Arctic char ( Salvelinus alpinus ) held in 90 m 2 littoral enclosures were estimated using bioenergetic (with consumption estimated using stable caesium, 133 Cs) and behavioural approaches (with fish movements quantified using video cameras). We found no statistically significant difference between values of activity rate obtained using the two approaches for three of the six experiments we performed. However, there was no relationship between estimates of activity rate obtained using the two approaches. Discrepancies may arise from the difficulty to meet assumptions regarding the temporal stability of the concentration of 133 Cs in fish diet and of the assimilation coefficient of this tracer. When fish remain in an area where their behaviour can be well described (e.g., enclosure, habitat patches of littoral zones, coral reefs), the behavioural approach appears more robust to estimate activity rate because it depends most on a variable that is easiest to estimate (the number of movements performed). When these conditions are not met (low fish densities or major fish migrations), a reliable assessment of the concentration and assimilation of 133 Cs in stomach contents appears critical to implement the bioenergetic approach based on this tracer.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →1 of 3 models called this metaresearch. This work is contested: it sits on the field's empirical boundary, and whether it counts depends on which model you asked. It is one of the 51 works in the disagreement dossier.
Comparison of bioenergetic and behavioural techniques for estimating fish activity; domain measurement validation, not a study of research practice.
The primary object is the comparative performance and robustness of two research methods for estimating fish activity.
Compares measurement approaches for fish activity rates to answer an ecological question, not to study research practice.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".