Comment on the second reply by Higdon to the comment by Romero and Kannada on “Genetic analysis of 16th-century whale bones prompts a revision of the impact of Basque whaling on right and bowhead whales in the western North Atlantic”Appears in Can. J. Zool. <b>86</b>(1): 76–79.
Bibliographic record
Abstract
The second reply by J.W. Higdon (2008. Can. J. Zool. 86: 76–79) criticizes a previously published comment by us of T. Rastogi et al.’s (2004. Can. J. Zool. 82: 1647–1654) paper saying that we presented factual errors, misused key sources, and made a number of omissions. The main objective of our original comment was to show that there had been many other peoples and nations besides the Basques who were engaged in whaling in the North Atlantic for many centuries and, therefore, the Basques could not have been solely responsible for anthropogenic impacts on the populations of large whales in that part of the world. To that end we only sampled some sources to make our point. In this rebuttal, we show that Higdon mischaracterizes our comment as a historical review and that neither he nor B.A. McLeod et al. (2006. Can. J. Zool. 84: 1066–1069) provide any evidence that challenges our fundamental conclusions.
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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 | 0.009 | 0.050 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.032 | 0.041 |
| Insufficient payload (model declined to judge) | 0.010 | 0.013 |
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".