Bibliographic record
Abstract
With waves crashing at break-neck speeds of up to 15 m s−1, life on the rocky coastline isn't easy, and residents of this intertidal zone continuously face the risk of wave-induced damage or death. Furthermore, they have to remain adaptable to ever-changing conditions arising from storms or seasonal changes, and may also move to new, potentially even harsher, shorelines in search of food. Pisaster ochraceus, the northeastern Pacific sea star, is amongst the largest of the intertidal inhabitants and Kurtis Hayne and his supervisor Richard Palmer from the University of Alberta, Canada, wondered how they might cope with changes in wave force (p. 1717).To investigate, Hayne set out from the lab's second base at the Bamfield Marine Sciences Centre, British Columbia, Canada, to collect sea stars from both exposed and sheltered shorelines on nearby islands. Back at base, Hayne then weighed and photographed the sea stars, using the images to measure the length and width of the sea stars' arms. Hayne found that, on average, sea stars collected from exposed sites had arm widths that were 12% narrower. They also had shorter arms and overall had a decreased mass per unit arm length.So, in exposed areas with fast, breaking waves, sea stars had thinner arms, but would they maintain their spindly shape if they were moved to a more sheltered spot? To find out, Hayne painted identifying marks on the sea stars before transplanting them onto new shorelines, moving sea stars used to the rugged sea to quieter locations and, vice versa, transplanting plumper sea stars with long, thicker arms onto more exposed spots. When Hayne returned after 3 months, he found that those he had moved to new neighbourhoods had changed to fit in with the new environment: previous inhabitants of sheltered shorelines reduced the width of their arms, while sea stars transplanted from exposed spots to calmer waters grew fatter arms. By changing their body shape according to their environments, sea stars may reduce drag and lift and thus the risk of dislodgement in exposed areas, while growth in calmer shores may help them to resist overheating and aid reproduction.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.046 | 0.021 |
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".