Factors that determine sperm precedence in ticks, spiders and insects: a comparative study
Bibliographic record
Abstract
INTRODUCTION There is a broad tendency among female insects for fecundity to increase with mating frequency (Ridley, 1988). A female's eggs carry forward to the next generation her genes and those of her mate(s). Hence, one might guess that promiscuity should be of selective advantage for both sexes. On closer inspection it is not as simple as that. The survival of a female's offspring is as much a function of her mate's fitness as it is of her own, so she has some interest in determining the paternity of her offspring (Birkhead, 1998; Eberhard, 1998; Wedell & Karlsson, 2003). On the other hand, how can the male's paternity be assured if his spermatozoa have to compete with those of other males in the same arena? In this chapter some of the mechanisms used by male insects that assure their paternity in this ‘promiscuous world’ are reviewed. These will be compared to what is known from the less extensive literature on ticks, with the object of determining whether there are lessons from insects that might point our way to future enquiries in ticks. SPERM PRECEDENCE AND PATERNITY Because of the proverbial battle of the sexes, as well as that among competing males, one encounters numerous mating strategies among terrestrial arthropods, and a fascinating literature on sperm competition to match. The degree to which sperm competition occurs in any instance is determined by a number of factors (reviewed extensively by Simmons & Siva-Jothy, 1998, and by Parker, 1998): (1) How readily will a previously mated female accept further males (sperm pre-emption)?
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".