Experimental tests of intercohort competition for food and cover in the tidepool sculpin (<i>Oligocottus maculosus</i> Girard)
Bibliographic record
Abstract
In the field, the tidepool sculpin, Oligocottus maculosus, has been observed to display a vertical intertidal distribution characterized by increasing mean standard length with decreasing distance above mean tidal height. It was hypothesized that this distribution is related to intercohort competition for food and (or) cover and, as a result, competi tive exclusion of smaller fish by larger fish from the lower pools. To test this hypothesis, several competition experiments were conducted that involved pairing O. maculosus from three size classes in a laboratory setting and observing their behaviour when presented with food or cover. When both fish attempted to procure food, the success rate of the larger fish was significantly higher than that of the smaller fish (Wilcoxon's signed-ranks test, T = 0, N = 6, p < 0.025). Furthermore, as the size difference between the two fish increased, the smaller fish made significantly fewer simultaneous attempts to procure the food (hierarchical log-linear test, partial χ2[5] = 28.326, p < 0.001), and utilized the cover significantly less (ANOVA, F[5] = 3.387, p = 0.008). The results from these experiments indicated that larger fish have a competitive advantage over smaller fish which extends to the acquisition of both food and cover. This is presumed to be the result of both greater competitive ability due to increasing size and an increased need for smaller fish to avoid detrimental aggressive interactions. In view of evidence from other papers indicating that the lower pools are more desirable to O. maculosus, it is suggested that intercohort competition is in part responsible for limiting the smaller fish to the upper tide pools.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".