Bibliographic record
Abstract
he Nahanni is a place touched by magic.The river enchants as it meanders past hot springs, through deep canyons, plunges over an enormous waterfall, and braids out into boreal forest.The landscape includes the stunning granite spires of the Cirque of the Unclimbables, vast karst features, and the extraordinary Ram Plateau.There are only a few places with such power on Earth.The Nahanni's magic touched me so deeply that I willingly devoted a good part of ten years to its protection.And I was far from alone.In the first decade of this century, Canadians packed auditoriums in Whitehorse, Halifax, Victoria, and many cities in between to hear about the glories and stories of the Nahanni.By the thousands they responded to the urgings of a collaboration of the Dehcho First Nations and the Canadian Parks and Wilderness Society (CPAWS) to join the chorus of musicians, scientists, public figures, canoe guides, businesses, and conservationists calling for its protection.It became so important to so many varied people that Parks Canada was able to successfully drive a park expansion through the labyrinth of mining interests inside government almost unscathed.The social movement we generated achieved that rarest of things: political consensus.The 2009 legislation to expand the park sped
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.458 | 0.317 |
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".