Summary information on Greenland halibut distribution in NAFO Subarea 2 and Divisions 3KLMNO
Bibliographic record
Abstract
This document has selected some spatial plots of survey and industry catch rates and catches to assist an understanding of the Greenland halibut distribution. Figure 1 shows the location of most of the Canadian catch of Greenland halibut in 2006 and 2007 (Brodie et al., 2008), while Figure 2 plots the distribution of Greenland halibut from Canadian fall surveys for these two years (Healey, 2008). Catch per haul distribution for the 2007 summer survey on Flemish Cap is shown in Figure 3 (Vázquez and González-Troncoso, 2008). Figure 4 plots the Spanish Scientific Observers Program data CPUE for 2001 to 2006 (GonzálezTroncoso, Sacau and González-Costas, 2007). Figures 5 and 6 show the distribution of catches based on the Spanish Scientific Observers Program data and Spanish survey data respectively (GonzálesCostas, pers. commn).
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".