American Fishcncs Society Symposium?:I-16. 1987 Use of Fish Eggs and Larvae in Probing Some Major Problems in
Bibliographic record
Abstract
Abstracr.Studies of the early life history of marine fishes have progressed greatly in the quarter century since the pioneering work of Sette, Ahlstrom, and others. A brief history of this recent era points out the many ways in which eggs and larvae have been used to address central problems of fishery dynamics, management, and culture. Challenges and opportunities await early life histori-ans in the areas of fish distribution, biomass estimation. species identification, recruitment, species interactions, aquaculture, enhancement, pollution assessment, definition of subpopulations, and production. Early life history studies have acquired considerable relevance to society as well as to science. I was pleased and flattered to be asked to be the keynote speaker to this meeting of the Early Life History section of the American Fisheries Soci-ety. The papers of this meeting are very impres-sive and comprehensive, much more so than those of the very first Larval Fish Conference in the United States, which was held at Lake Arrow-
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.146 | 0.070 |
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".