A comparison of gut evacuation models for larval mackerel (<i>Scomber scombrus</i>) using serial photography
Bibliographic record
Abstract
A novel technique is described, using serial photography of the gut contents of transparent living larval fishes, to generate individual gut evacuation time series. This technique was applied to Atlantic mackerel Scomber scombrus larvae to compare three widely used models of gut evacuation: linear, exponential and square-root. Regression r(2) for the exponential model exceeded those for the linear and square root models in 20 of 21 time series, strongly supporting the exponential model. At the initial gut fullness for each time series, total gut evacuation rates calculated with the exponential model averaged 2.2 and 1.3 times greater than those calculated with the linear and square-root models, respectively, and would produce correspondingly higher estimates of feeding rates for field-collected larvae with similar levels of gut fullness. The results highlight the importance of choosing the appropriate evacuation model in feeding studies, particularly those intended to examine short-term changes in larval fish feeding rates, a contributing factor to the highly variable yearly recruitment of many marine fish species.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".