Traditional and geometric morphometric data describing wild and artificially reared cisco (Coregonus artedi) from lakes Huron and Ontario
Bibliographic record
Abstract
These data describe morphometric (body shape) measurements of wild and artificially reared (i.e., raised in a laboratory or fish hatchery) cisco (Coregonus artedi) from lakes Huron and Ontario in the Laurentian Great Lakes. Specifically, this data release includes traditional morphometric data (i.e., measurements of fish specimens) describing wild and artificially reared cisco from Lake Huron, as well as geometric morphometric data (i.e., landmarks placed on images of fish) describing cisco head shapes for wild and artificially reared cisco from both lakes Huron and Ontario. Artificially reared individuals from Lake Huron were raised at the U.S. Geological Survey Great Lakes Science Center in Ann Arbor, MI, USA, and one family of offspring were split among three rearing temperature treatments. Artificially reared individuals from Lake Ontario were raised at the Tunison Laboratory of Aquatic Science in Cortland, NY, USA. These data were collected by the authors on this data release from 2017-2023 and used to analyze the impacts of artificial rearing on cisco body shapes, with a focus on head shapes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.009 |
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".