To invest or not to invest, that is the question: male presence and genetic relatedness as modulators of female reproductive effort in a shrimp
Bibliographic record
Abstract
The present work was aimed at evaluating whether females of a freshwater shrimp, Neocaridina davidi (Bouvier, 1904), allocate differentially to reproduction when reared in the presence of males and in the presence of brothers/non-brothers. Ovarian growth was evaluated in three consecutive maturation cycles. The composition of biochemical reserves was determined in the eggs (i.e., embryos) laid at the end of the first cycle, in 20-day-old juveniles produced at the end of the second cycle, and in the mature ovary of females at the end of the third cycle. When reared in the absence of males, females took longer to mature the ovaries and stored less proteins, triglycerides, and cholesterol in the mature ovary. Females reared with brothers took longer to mature the ovaries than females reared with non-brothers, with no differences in the biochemical composition of their mature ovaries. The eggs produced by females mated to brothers showed a lower carotenoid content, higher cholesterol content, and a tendency towards lower energy content than those produced by females mated to non-brothers. These results suggest that females are capable of recognizing kin and modulate primary reproductive effort, in terms of ovarian and egg biochemical composition, according to male presence and genetic relatedness.
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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 | 0.000 | 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".