Reproductive patterns and energy management strategies of females of the fiddler crab <i>Leptuca uruguayensis</i> with short reproductive seasons
Bibliographic record
Abstract
Reproduction is a costly process that depends on the management of available resources. Here, we aimed to understand the energetic strategies of females of the fiddler crab Leptuca uruguayensis (Nobili, 1901) in a population with short reproductive seasons. For this, we developed an integrated approach to recognize the brooding time, spawning pattern modulated by female size, number of spawns per female, and content of reserves in the ovary and hepatopancreas. Based on the condition of the ovary and hepatopancreas, the reproductive season was divided into three periods. In each of these periods, it was possible to record a spawning event, which was mainly represented by large females. Most of the females had one spawn during the breeding season, and only large females had two spawns, with an interval of approximately 2 months. We propose that L. uruguayensis presents a mixed capital–income breeding strategy associated with the female size and period of the reproductive season. We conclude that large females make the greatest reproductive effort for the population because they can have two spawns, whereas medium-sized and small females make a low contribution because they are still investing energy in somatic growth to increase fecundity in the next reproductive season.
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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 | 0.000 |
| 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".