Southern king crab larval survival: from intra- and interfemale variations to a fishery-induced mortality
Bibliographic record
Abstract
The southern king crab (Lithodes santolla) supports one of the most important fisheries in southern South America. Lecithotrophic larvae hatch over an extended period, in which brooding females can be fished, but must be discarded due to regulations. Larval mortality by female fishing was evaluated. Samples of newly hatched zoeae I were obtained the day before (control) and after female treatment (aerial exposure or aerial exposure + free fall). Independently of the mothers’ treatment, larvae survived less than those from the control, explained by the air-exposure effects. The intraclutch variability in larval survival and their variability in energetic reserves were studied. Females were maintained during the hatching period, and zoea I samples were taken during 3 successive days. We found high variation in larval survival within a single egg clutch and between different females, only ascribable to the initial larval glycogen content. The intraclutch variability in larval survival combined with extended hatching may be an adaptation that allows mothers to find an adequate substrate as larvae hatch and may constitute a diversified bet-hedging strategy.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".