Habitat selection, movement patterns, and demography of common musk turtles (Sternotherus odoratus) in southwestern Québec
Bibliographic record
Abstract
I studied the common musk turtle (Sternotherus odoratus) at the northern limit of its range at Norway Bay, Quebec, from April to October 2006. Common musk turtles are habitat specialists and are selective of their habitats at the study-area and home-range scales. Beaver ( Castor canadensis) lodges were preferred at the study-area scale. Common musk turtles also preferred beaver lodges, emergent wetlands, aquatic beds with floating and submerged vegetation as well as rocky shores at the home-range scale. At the location scale, common musk turtles chose shallower and cooler sites that contained more logs and submerged vegetation than the sites available at random. There was no significant effect of sex on habitat use at the location scale. There was no significant difference in mean daily movements between the sexes during the active season. However, sex and month probably interact together to influence the mean distance traveled daily by common musk turtles in Norway Bay. Males appeared to move more than females in May, July, and October. Females appeared to move more daily than males in August and September. Neither sex appeared to move more daily in June. However, our small sample size did not allow us to conduct a conclusive analysis. The mean home-range area was 23.9 ha and was not different between sexes. I estimated a density of 4.1 turtles/ha and a sex ratio of 1.7M: 1F. The population includes 59.6% males, 35.8% females, and 4.6% juveniles. Adults ranged from 77 mm to 133 mm in carapace length.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".