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
Prime Arctic predator and nomad of the sea ice and tundra, the polar bear endures as a source of wonder, terror, and fascination. Humans have seen it as spirit guide and fanged enemy, as trade good and moral metaphor, as food source and symbol of ecological crisis. Eight thousand years of artifacts attest to its charisma, and to the fraught relationships between our two species. In the White Bear, we acknowledge the magic of wildness: it is both genuinely itself and a screen for our imagination. Ice Bear traces and illuminates this intertwined history. From Inuit shamans to Jean Harlow lounging on a bearskin rug, from the cubs trained to pull sleds toward the North Pole to cuddly superstar Knut, it all comes to life in these pages. With meticulous research and more than 160 illustrations, the author brings into focus this powerful and elusive animal. Doing so, he delves into the stories we tell about Nature—and about ourselves—hoping for a future in which such tales still matter.
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.
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 | 0.000 | 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 | 0.000 | 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 it