Bibliographic record
Abstract
I called Marine and Freshwater Miscellanea I (FCRR 26(2)), a “vinegret* of contributions covering a variety of fish and fishery related topics” from Dr. Daniel Pauly. In this, the second collection of articles by Pauly and colleagues that were deemed not suitable for peer-reviewed scientific journals, but which readers may find of interest, it is less of a salad course and more of a meal. There is very little that Daniel Pauly writes that is not of interest to fisheries researchers, whether peer-reviewed or not. Such are the trials of a man whose lifetime of work has been so foundational in the fields of fisheries science and biodiversity research. We should all aspire to such tribulations. Here, Dr. Pauly pays homage two of his mentors, as well as with his colleagues sharing articles that range from marine biodiversity in the Indo-Pacific to fisheries management in the Small-Island States, from marine mammals in the Sea of Okhotsk to the Gill-Oxygen Limitation Theory (GOLT). The topics are widespread, but all are interesting, and I invite you to enjoy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.042 | 0.008 |
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".