Drift probabilities for Icelandic cod larvae
Bibliographic record
Abstract
Abstract Brickman, D., Marteinsdottir, G., Logemann, K., and Harms, I. H. 2007. Drift probabilities for Icelandic cod larvae – ICES Journal of Marine Science, 64, 49–59. The climatological distribution of juvenile Icelandic cod is characterized by a negative spatial age gradient, with a fairly abrupt decrease in age near the northwest corner of Iceland, and a spatial abundance gradient with higher concentrations of 0-group fish inshore. Flowfields from a high-resolution circulation model developed for Icelandic waters were used to investigate larval drift from the various spawning grounds in Icelandic coastal waters to understand the distribution of 0-group fish. To present the results clearly, drift probability density functions (pdfs) are derived describing the probability of drifting from a given spawning ground to a given spatial region over a specified time interval. These pdfs are used to determine the spawning grounds most probably contributing to the observed age distribution. The observed spatial gradient in age is likely due to differences in the spawning location of larvae, with older larvae originating in spawning grounds in the southwest and younger larvae from farther north. In general, the contribution from the main spawning grounds in the southwest is predicted to decrease with clockwise distance from the source region. The pdf technique was also used to investigate drift from regions on the south coast of Iceland corresponding to known or possible subpopulation spawning grounds, to see whether these spawning areas are associated with distinct drift patterns. This technique is a useful way to present larval drift results and to facilitate comparison with real data.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".