Is sperm viability independent of ejaculate size in the house cricket (<i>Acheta domesticus</i>)?
Bibliographic record
Abstract
Assessing sperm viability is a popular means of testing hypotheses related to ejaculate quality. This technique has produced interesting results; however, the sperm viability assay itself may kill sperm. This is a serious pitfall, as assay-related mortality could confound results and produce artificially low estimates of viability. To avoid spurious results, it has been recommended that investigators include sperm number in their viability analyses. Unfortunately, studies conducted to date on internal fertilizers have not included sperm counts in their analyses, so it is not possible to assess whether this factor can indeed produce artefactual results. In this paper, we use male house crickets ( Acheta domesticus (L., 1758)) to show that sperm viability is dependent on sperm number and exclusion of this factor from statistical analyses affects our interpretation of experimental treatment results. We show that mechanically rupturing a spermatophore significantly reduces sperm viability, but this does not appear to drive the nonindependent relationship between viability and number. Instead, our study shows that nonindependence is due to processes other than differential physical damage to the sperm during collection. We also show that allowing a spermatophore to evacuate its sperm without rupturing for 10 min maximizes both sperm number and viability.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".