Use of otolith shape to inform stock structure in Patagonian toothfish (Dissostichus eleginoides) in the south-western Atlantic
Bibliographic record
Abstract
An analysis of patterns in otolith shape is an effective tool for discriminating among fish stocks. Otolith shapes of Patagonian toothfish (Dissostichus eleginoides) and Antarctic toothfish (D. mawsoni) were investigated for geographic variability within seven regions across the Patagonian Shelf, and South Georgia and the South Sandwich Islands (SGSSI). Otolith shape was characterised by its elliptical Fourier coefficients (EFCs), corrected for fish length before being analysed, using multivariate methods. Non-metric multidimensional scaling analysis suggested the following three main groupings: Patagonian Shelf, SGSSI, and the third for Antarctic toothfish. This result was supported by ANOVA-like permutation tests, indicating significant (P < 0.001) differences in otolith shape among these three groupings. Linear discriminant analysis (LDA) cross-validation analyses of the EFCs resulted in otoliths being correctly classified to the sampling region from which they came, with an accuracy ranging from 78.95 to 100%. LDA cross-validation analyses on sampling regions within SGSSI and the Patagonian Shelf were able to classify individuals back to their sampling region with an accuracy of greater than 89.74 and 78.95% respectively. These results have provided some alternative insights into the stock structure of Patagonian toothfish across southern South America, South Atlantic and SGSSI.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".