Contrasting Global Game Fish and Non-Game Fish Species
Why this work is in the frame
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Bibliographic record
Abstract
ABSTRACT: We compared biological and ecological traits between global game fish and non-game fish species using an analysis with randomly chosen fish species from each group and an analysis where species were matched by body length. We used data from the International Game Fish Association (IGFA), FishBase, and the International Union for Conservation of Nature (IUCN) Red List of Threatened Species. Game fish species were defined as being present in the IGFA world record list. The random comparison revealed that on average game fish were significantly larger (155.0 ± 121.5 versus 34.1± 59.5 cm), occupied shallower minimum depths (19.4 ± 58.8 versus 130.0± 359.0 m), had a broader latitudinal range (51°.2 ± 29.4° versus 31.1°± 25.9°), and significantly higher trophic levels (4.1 ±0.1 versus 3.4± 0.1 trophic units) than non-game fish species. The length-matched analysis simüarly identified that game fish species occupied higher trophic levels than non-game fish (3.9 ± 0.4 versus 3.6± 0.6 trophic units), but latitudinal range and depth associations did not differ between groups. Both the random and length-matched analyses revealed that game fish were more commonly found in freshwater than non-game fish. Both analyses found that game fish species were more migratory and that both groups differed in their geographical distributions. The random comparison revealed that game fish were significantly more targeted by commercial fisheries, less resilient, and more threatened relative to non-game fish. Caution must be exercised when synthesizing data from broad data sources, yet this study identifies important differences between game fish and non-game fish species, which are relevant to management and conservation initiatives.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 it