Movement patterns in the green sea urchin, <i>Strongylocentrotus droebachiensis</i>
Bibliographic record
Abstract
Time-lapse video was used to record movement paths of Strongylocentrotus droebachiensis on a rocky bottom at 8 m depth, both at a grazing front and in recently formed barrens in the wake of the front. Urchins did not exhibit strong directionality in movement and we did not detect any differences in movement variables between the front and barrens. Density of conspecifics had a negative effect on the speed, move length (distance), and daily displacement of urchins, but did not significantly affect the proportion of time spent moving, the linearity index and the number of moves taken per day. The frequency distributions of turning angles between moves and steps were non-uniformly distributed, indicating directionality in individual paths. A correlated random walk model was used to predict the displacement of urchins through time and provided a good fit with observed data. Our results provide insight into the foraging behaviour of S. droebachiensis and are consistent with previous observations of small-scale movement in this species.
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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 | 0.000 | 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 | 0.000 |
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".