Bibliographic record
Abstract
Background. Fishes are important both economically and as indicators of environmental health. Questions on the health of aquatic habitats, on the potential effects of planned and accidental changes to the environment, and on the utility of adding sport and other fishes to a water body are best answered by an analysis which is known to be sensitive to changes. Materials and methods. As an initial test study I examined 107 fish species in and around the National Capital Region of Canada (50 km radius of the Peace Tower at the Parliament Buildings) in terms of 56 parameters. The parameters include life history characteristics such as size, lifespan, breeding season, egg numbers, and feeding, as well as zoogeographic origins, distribution, and risk status. Non-parametric tests and a logistic regression were used to analyze the data. Results. A test case comparison of sport versus non-sport fishes confirmed the empirical observation that sport fishes are predominately large piscivores. Critical parameters for threatened versus non-threatened species included piscivory and egg production, for present versus absent species feeding habits and refugial origin, and for refugial origin parameters associated with spawning. Conclusion. The parameter database can be of potential use to determine which species are at risk and which parameters are critical, why certain species are absent, and what parameters characterize sport fishes. The analysis forms a preliminary basis for more detailed field studies which can then be directed to specific life history traits and environmental variables.
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How this classification was reachedexpand
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".