Thick-billed murre Patterson Coats meps13890
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
Climate change is altering the marine environment at a global scale, with some of the most dramatic changes occurring in Arctic regions. These changes may affect the distribution and migration patterns of marine species throughout the annual cycle. Species distribution models have provided detailed understanding of the responses of terrestrial species to climate changes, often based on observational data; biologging offers the opportunity to extend those models to migratory marine species that occur in marine environments where direct observation is difficult. We used species distribution modelling and tracking data to model past changes in the non-breeding distribution of thick-billed murres Uria lomvia from a colony in Hudson Bay, Canada, between 1982 and 2019. The predicted distribution of murres shifted during fall and winter. The largest shifts have occurred for fall migration, with range shits of 211 km west and 50 km north per decade, compared with a 29 km shift west per decade in winter. Regions of range expansions had larger declines in sea ice cover, smaller increases in sea surface temperature, and larger increases in air temperature than regions where the range was stable or declining. Murres migrate in and out of Hudson Bay as ice forms each fall and melts each spring. Habitat in Hudson Bay has become available later into the fall and earlier in the spring, such that habitat in Hudson Bay was available for 21 d longer in 2019 than in 1982. Clearly, marine climate is altering the distribution and annual cycle of migratory marine species that occur in areas with seasonal ice cover.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.055 |
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