Data and code from: Thermal niche and habitat use by co-occurring lake trout (Salvelinus namaycush) and brook trout (S. fontinalis) in stratified lakes
Bibliographic record
Abstract
Realized thermal niche and habitat use are two conceptualizations of fish habitat based on organismal performance or lake-specific ecology, respectively. Both habitat types were compared for lake trout (Salvelinus namaycush) and brook trout (S. fontinalis) co-occurring in four large (> 500 ha) oligotrophic lakes. Lakes were partitioned into two morphological categories based on possession of a central or non-central deep basin with corresponding differences in adjoining shelf areas. Lake asymmetry in basin location has been shown to strongly influence food web connections based on isolation of basins from shelf areas. Generally, overlap between both habitat types occurred in several comparisons with lake trout, suggesting that thermal habitat is a reasonable proxy for habitat use boundaries though not a full replacement for insights gained from habitat use models. For brook trout, overlap was not as consistent, especially for lakes with non-central basins. In central basin lakes, there were closer proximity between the two species and overlap in both thermal niche and habitat use models. There was very limited overlap of either habitat type in lakes with non-central basins. Further, there were no shared areas of interspecific overlap between thermal niche and habitat use in non-central basins pointing to additional complexity governing habitat partitioning between lake trout and brook trout in these types of lakes. The shelf area effect on spatial structure of habitat, and likely food web connections, can occur in lakes regardless of basin centrality so long as shelf areas are large. In this lake set, lakes were sufficiently large to observe this phenomenon.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.198 | 0.067 |
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".