Biology and Management of Dogfish Sharks
Bibliographic record
Abstract
Abstract.—The first tagging program for spiny dogfish <em>Squalus acanthias </em>in Washington State was conducted in the early 1940s, coinciding with the period of the highest landings in the history of the fishery, when annual landings in the Northeast Pacific grew to over 50,000 metric tons (mt). A second tagging program in Puget Sound began in 1969, when landings in the Northeast Pacific were below 500 mt. Patterns of recaptures from the two tagging experiments are reanalyzed and compared using a common set of spatial areas for the first time. The fraction of dogfish remaining in each basin and moving between each pair of basins is reported, along with the fraction of dogfish recaptured in Canadian waters. Seasonal movement north and south in coastal waters is considered. Differences in length compositions between inside and outside waters are described, and possible causes of this difference are discussed. The potential use of these tagging results in a population dynamics model is considered.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.004 |
| 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 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".