Diversity of deep-water cetaceans and primary productivity
Bibliographic record
Abstract
Recently, it has been suggested that mammal diversity both on land and in the sea is controlled by patterns of primary productivity.Here we tested the hypotheses that large-scale patterns of marine mammal diversity are linked to primary productivity, sea surface temperature (SST) or a combination of these 2 factors.We used a consistently sampled sightings database of deep-water cetaceans in the Atlantic and Pacific Oceans, along with in situ SST measurements and 3 satellite-derived productivity measures matched spatially and temporally to available sightings.Cetacean genus richness peaked in regions of high primary productivity (>1000 to 1500 mg C m -2 d -1 ), but most of this effect is captured by optimal SST in those same regions.Our results show that the best-supported, explanatory models of cetacean diversity included SST, while the addition of satellitederived measures of productivity did not improve predictive capacity.Marine mammal richness globally peaks around 40° N and S, and may result more directly from optimal SST at these latitudes rather than high oceanic productivity.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".