It’s a shark-eat-shark world, but does that make for bigger pups? A comparison between oophagous and non-oophagous viviparous sharks
Bibliographic record
Abstract
Abstract Oophagous reproduction (i.e., consumption of unfertilized ova in utero) in sharks has been hypothesized to result in fewer but larger pups relative to those produced by viviparous sharks with different modes of maternal nutrient transfer. We compared pup and litter sizes reported in the literature for 106 shark species with lecithotrophic viviparity, oophagy, and placental viviparity as methods of maternal nutrient transfer during pregnancy. Using a suite of permutational tests, we accounted for the effect of maternal size to test whether oophagous strategies do indeed result in larger pups and smaller litters relative to sharks with lecithotrophic and placental viviparous reproduction. Our results demonstrated that litter size was significantly reduced in species with oophagous reproduction relative to sharks with lecithotrophic and placentally viviparous reproduction. Further, the influence of oophagous reproduction on pup length was more variable, and generally pup length of oophagous species was only larger than sharks with lecithotrophic viviparous reproduction. However, when maternal investment was expressed as litter mass (minimum pup mass by litter size), the effect of oophagy was neutralized. We found further evidence that pup length at birth was directly modulated by litter size and habitat, suggesting pup length at birth may also be adapted to conditions at nursing grounds. Our study supports the hypothesis that both placentally viviparous and lecithotrophic viviparous species maximize their reproductive fitness by allocating nutrients to larger litters of pups, whereas oophagous species maximize reproductive fitness through smaller litters of pups that may be well adapted to their nursing grounds.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".