Female life-history traits of a species pair of threespine stickleback in Mud Lake, Alaska
Bibliographic record
Abstract
Aim: Compare several female life-history traits in a stickleback species pair (i.e. size and age at reproduction, clutch size, egg mass, and reproductive effort) to determine whether time during the reproductive season (early or late) or breeding habitat (vegetation, open sites) significantly affect trait values. Organisms: Sympatric ecotypes of anadromous and resident freshwater threespine stickleback (Gasterosteus aculeatus). Time and place: Mud Lake, Cook Inlet region, Alaska, May–July 2003. Results: Both resident and anadromous fish in Mud Lake bred primarily at age 2. Anadromous breeders were larger than resident breeders. Size of reproductive females declined from early to late in the breeding season for both anadromous and resident freshwater populations, but time and breeding habitat were not significant sources of variation in most life-history traits. Clutch mass showed a similar, positive correlation with female body mass in both populations, but clutch size (fecundity) rose more slowly with female size in resident fish. Both ecotypes made eggs of similar size overall, with egg size in resident females increasing modestly with female body size. Both ecotypes showed a trade-off between clutch size and egg mass after adjustment for the level of reproductive effort. The egg mass and clutch mass of both ecotypes were small compared with other Cook Inlet resident and anadromous populations.
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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 | 0.001 | 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".