Bibliographic record
Abstract
Statement I have been privileged to travel and work throughout the northern wilderness, initially as a biologist and wilderness guide and now as an artist. Twice I have been surrounded by thousands of the Porcupine Caribou herd migrating across the Firth and the Malcolm Rivers and I have drawn on these experiences to create this work. For me, caribou symbolize not only the expanse of wild land required to sustain an intact ecosystem but also the fragility of the northern boreal and Arctic ecosystems. Many caribou herds are in decline and some, such as the Porcupine Caribou herd, which migrates between the Yukon and Alaska, have their critical calving habitat threatened by oil development. I hope my work can raise awareness about the issues surrounding resource development and extraction in critical wildlife habitats. Arctic environments may seem resilient but they are in fact quite fragile and don't recover well from disturbance. I never tire of watching these icons of the North float over the land. They are insatiably curious, seemingly goofy at times, but ultimately caribou are the most graceful creatures on the tundra.
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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.087 | 0.029 |
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".