Bibliographic record
Abstract
Piles of bison skulls were a common sight on the Canadian prairies in the late nineteenth century 29 Transplanted yaks in Buff alo National Park, Alberta 30 Visitors to Canada's national parks were often encouraged to feed the animals 31 Warden Davison with his pet elk Maud at Buff alo National Park 32 Mr. Campbell McNab and his hunting trophies 38 An Alberta game warden nabs a poacher near Hardisty 56 An Aboriginal hunting guide with his kill 65 "Jack Miner: The Pioneer Naturalist" comic strip, part 1 67 "Jack Miner: The Pioneer Naturalist" comic strip, part 2 106 James Watt oversees the live trapping and transfer of beaver at the Charlton Island Preserve 107 The Hudson's Bay Company hired young Aboriginal men at its Attiwapiskat Preserve to carry out its conservation program 109 Three kids and three kits at Rupert's House 112 Grey Owl's Lake Ajawaan cabin was a duplex, housing him and his wife Anahareo, along with his pet beavers 115 Grey Owl models the latest in outdoors fashion: the Saskatchewan beaver stole 118 Map of beaver preserves in northern Quebec 133 The photograph that triggered the "caribou crisis" in Canada's North 142 Roundups were commonplace at some of Canada's animal parks from the 1930s to the 1960s 150 Killing gophers was a part of everyday life for boys like James Ray Hartman 151 Nine-year-old George Burns and his dog relax after a day of coyote killing 168 In British Columbia cougar hunters were important members of rural society 170 Vancouver Island's "Cougar" Cecil Smith 182 In the years after the Second World War, the wilderness was more accessible to armed tourists looking for a sporting holiday
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.792 | 0.672 |
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".