Bibliographic record
Abstract
Though narwhal have survived multiple ice ages, including 2.5 Ma and the last interglacial period with warming temperatures, Arctic climate change during the Anthropocene introduces new challenges. Despite their evolutionary connection to Arctic Pleistocene fossils, narwhal archeocete ancestors from the Pliocene ( Bohaskaia monodontoides ) and Miocene ( Denebola and Odobenocetopsidae) inhabited warm waters. Narwhal Arctic adaptation holds valuable insights into unique traits, including thin skin; extreme diving capacity; and a unique straight, spiraled, and sensory tooth organ system. Inaccessible weather, ice conditions, and darkness limit scientific studies, though Inuit knowledge adds valuable observations of narwhal ecology, biology, and behavior. Existing and future studies in myriad fields of physical, chemical, biological, and genetic science, combined and integrated with remote sensing and imaging technologies, will help elucidate narwhal evolution, biology, and adaptation. When integrated with Qaujimajatuqangit, “the Inuit way of knowing,” these studies help describe interesting biologic expressions of the narwhal.
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.
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 | 0.000 | 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 | 0.003 | 0.004 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".