Thermal stress and morphological adaptations in limpets
Bibliographic record
Abstract
1 On thermally stressful rocky shores, small, slow-moving ectotherms such as limpets exhibit morphological characteristics such as high-spired and heavily ridged shells which may reduce the likelihood of reaching stressful or lethal body temperatures. 2 The effects of shell height and shell surface area on predicted limpet body temperatures were tested with a previously developed heat budget model. The model was parameterized with morphological data from three species (Lottia gigantea, Patella vulgata and Siphonaria gigas), which differ dramatically in their morphology and in the body temperatures they are likely to reach in the field. 3 Limpet models and standard cones with higher height : length ratios lost heat to convection more readily than models with lower spired shells. 4 Heavily ridged shells lost heat to convection more readily than smoother shells, but this effect was only pronounced at high wind velocities. 5 When the heat budget model parameters were applied to a real environmental data set, the model predicts that maximum body temperatures and cumulative thermal stress vary among species. These differences are related primarily to the height : length ratio of the shell, and to a lesser extent to the presence of ridges. 6 These results suggest that some intra- and interspecific variation in limpet morphology may be phenotypic or evolutionary responses to variation in environmental temperatures. Our findings are supported by observed patterns of limpet morphological variation across natural thermal gradients.
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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 | 0.001 | 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".