Size, growth, and density data for shallow‐water sea urchins from Mexico to the Aleutian Islands, Alaska, 1956–2016
Bibliographic record
Abstract
Size, growth, and density have been studied for North American Pacific coast sea urchins Strongylocentrotus purpuratus, S. droebachiensis, S. polyacanthus, Mesocentrotus (Strongylocentrotus) franciscanus, Lytechinus pictus, Centrostephanus coronatus, and Arbacia stellata by various workers at diverse sites and for varying lengths of time from 1956 to present. Numerous peer-reviewed publications have used some of these data but some data have appeared only in graduate theses or the gray literature. There also are data that have never appeared outside original data sheets. Motivation for studies has included fisheries management and environmental monitoring of sewer and power plant outfalls as well as changes associated with disease epidemics. Studies also have focused on kelp restoration, community effects of sea otters, basic sea urchin biology, and monitoring. The data sets presented here are a historical record of size, density, and growth for a common group of marine invertebrates in intertidal and nearshore environments that can be used to test hypotheses concerning future changes associated with fisheries practices, shifts of predator distributions, climate and ecosystem changes, and ocean acidification along the Pacific Coast of North America and islands of the north Pacific. No copyright restrictions apply. Please credit this paper when using the data.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 teacher head, 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".