Comments in response to “Estimating the energetic contribution of polar bear (Ursus maritimus) summer diets to the total energy budget” by Dyck and Kebreab (2009)
Bibliographic record
Abstract
Dyck and Kebreab (2009) analyzed the required summer intake of arctic char, ringed seal blubber, and berries that polar bears must consume to maintain their body mass during a summer ice-free period. Their calculations of required intake were based on the amount of body mass lost by fasting bears in western Hudson Bay. However, fasting polar bears are in a low metabolic state with energetic requirements less than those of an active, feeding bear. Estimates of energy consumed by captive brown bears were 4–4.5 times higher than the estimates used by Dyck and Kebreab for similar diets. Furthermore, the authors' portrayal of the availability of these resources is misleading because they do not acknowledge limited accessibility of arctic char due to their limited anadromy and predominant occurrence in streams too deep to facilitate efficient capture by polar bears; effects of large interannual fluctuations in the availability of berries or competition with other frugivores; high energetic requirements associated with lengthy foraging times required to locate and consume sufficient fruit; and data from southern Hudson Bay, western Hudson Bay, and the southern Beaufort Sea that document continued declines in several biological indices over the past several decades despite the authors' suggested availability of terrestrially based food resources. Based on current information, arctic char, berries, and ringed seals in open water do not appear to be food sources with the potential to offset the nutritional consequences of an extended ice-free period.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".