F I G U R E 5 in Incorporating vertical movement of fishes in habitat use models
Bibliographic record
Abstract
F I G U R E 5 Daily habitat volume estimates across vswim quantile values (50th, 75th, 95th, and 100th) and vswim selection method (all vs. fish-season). The "all" habitat volume estimates were obtained using the entire distribution of daily movement speeds, whereas the "season-specific" daily habitat volume estimates were obtained using vswim values that were specific to every possible fish-season combination. The middle line in each box plot represents the median habitat volume value, with the boxes representing the interquartile ranges (IQR) for each distribution. The top and bottom of the boxes are the first and third quartiles (Q1 and Q3), respectively. The whiskers extend from Q1 and Q3 to the smallest and largest values, respectively, with a maximum length of 1.5 * IQR. Outliers outside of the whiskers are shown with black points.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.004 |
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".