Bibliographic record
Abstract
The subject of reproductive potential of fish populations is dominated by studies on the female gender. Studies on male reproduction are relatively few, but have increased in number during the previous decade. The objectives of this contribution were to describe and quantify the reproductive traits that make up the viable sperm production of a population. Some of these reproductive traits were easily measured from wild fish (e.g., mature testes weight), and others were more easily measured on captive fish (e.g., fertilization potential and sperm motility). Results of laboratory and field studies were then integrated to generate estimates of viable sperm production of a fish stock. A number of experimental protocols have been employed over the years to assess male fertility. The strengths and weaknesses of the different experimental approaches were reviewed and appropriate recommendations given towards establishing standardized protocols. Although the review is broad in nature, and includes references to a number of marine fishes, it concentrated on exploited species that occur in the North Atlantic and Baltic Sea within the taxonomic groups gadoidae, pleuronectoidae and clupeidae (Clupeiformes). In addition, published data on male reproductive traits of species in these taxa were tabulated and summarized. The terms of interest included sex ratio, maturity state, testes weight, sperm fertilization potential (artificial fertilization and paired mating), sperm density, sperm motility and paternal effects on early life history traits.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".