Biografía. D. Francisco Martínez y Laso de la Vega, el Indiano
Bibliographic record
Abstract
Kelps are a clade of morphologically diverse, ecologically important habitat-forming species. Many kelps live in wave-swept environments and are exposed to chronic flow-induced stress. In order to grow and survive in these harsh environments, kelps can streamline (reducing drag coefficient) to avoid drag or to increase attachment and breakage force to tolerate it. We aimed to quantify the drag tolerance and streamlining strategies of kelps from wave-swept intertidal habitats. We measured drag coefficient and tenacity of populations from eight kelp species over a wide range of sizes to determine whether kelps avoid dislodgement by reducing drag coefficient or by increasing tenacity as they grow, and whether these traits are traded off. We employed phylogenetic comparative methods to rule out potentially confounding effects of species' relatedness. There was a significant negative relationship between drag avoidance and tolerance strategies, even after incorporating phylogeny. Kelps that were more tenacious were less able to reduce drag, resulting in a continuum from "tolerators" to "streamliners," with some species demonstrating intermediate, mixed strategies. Drag and tenacity were correlated with geometric properties (i.e., second moment of area) of the stipe in large kelps. Results presented in this study suggest that kelps are either strong or streamlined, but not both. This continuum is consistent with avoidance and tolerance trade-offs that have been documented in many different biological systems and may have widespread implications for the evolution of large macroalgae, perhaps driving morphological diversity within this group.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 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 | 0.001 |
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; both teacher heads agree on what is shown here.
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".