Common Musk Turtles (Sternotherus odoratus) select habitats of high thermal quality at the northern extreme of their range
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract In ectotherms, variation in body temperature (Tb) affects physiological performance and, ultimately, fitness. Therefore, reptiles regulate Tb behaviourally by choosing habitats of optimal temperature. The main goal of this study was to determine the link between patterns of thermoregulation and habitat selection in Common Musk Turtles inhabiting a thermally challenging region. We expected habitat selection to be based on the fulfillment of thermoregulatory requirements, which can be accomplished by selecting thermally superior habitats. From early May to late August 2007, we tracked 22 Common Musk Turtles with temperature-sensitive radio-transmitters and collected daily Tb profiles with automated radio-telemetry data loggers. In addition, temperature data loggers were placed in the study area to measure the range of environmental operative temperatures (Te) available to musk turtles. The habitats with the highest thermal quality were aquatic habitats with surface cover (i.e., lily pads, macrophytes, etc.) followed by shallow water. As expected, musk turtles used habitats non-randomly and had a strong preference for thermally superior habitats. This is consistent with the typical aquatic basking behaviour observed in musk turtles, suggesting that there is a strong link between thermal quality of habitats and habitat selection, even in this almost entirely aquatic turtle.
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.
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 | 0.001 | 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 | 0.001 |
| 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 it