Condition-dependent ejaculate size and composition in a ladybird beetle
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Sexually selected male ejaculate traits are expected to depend on the resource state of males. Theory predicts that males in good condition will produce larger ejaculates, but that ejaculate composition will depend on the relative production costs of ejaculate components and the risk of sperm competition experienced by low- and high-condition males. Under some conditions, when low condition leads to poorer performance in sperm competition, males in low condition may produce ejaculates with higher sperm content relative to their total ejaculate and may even transfer more sperm than high-condition males in an absolute sense. Previous studies in insects have shown that males in good condition transfer larger ejaculates or more sperm, but it has not been clear whether increased sperm content represents a shift in allocation or simply a larger ejaculate, and thus the condition dependence of ejaculate composition has been largely untested. We examined condition dependence in ejaculate by manipulating adult male condition in a ladybird beetle (Adalia bipunctata) in which males transfer three distinct ejaculate components during mating: sperm, non-sperm ejaculate retained within the female reproductive tract, and a spermatophore capsule that females eject and ingest following mating. We found that high condition males indeed transferred larger ejaculates, potentially achieved by an increased rate of ejaculate transfer, and allocated less to sperm compared with low-condition males. Low-condition males transferred ejaculates with absolutely and proportionally more sperm. This study provides the first experimental evidence for a condition-dependent shift in ejaculate composition.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it