Bibliographic record
Abstract
Writing this guide would have been impossible without the help of the dozens of people who have, over the past sixteen years, given us practical support and provided us with information.To the extent possible, we here wish to acknowledge and thank those persons.We will undoubtedly miss naming some who have helped us along the way, and we apologize for this oversight.The help of all contributors, named or unnamed, has been appreciated.Thanks first to Gene Josephson and Wendy Stueck who accompanied us down the Clearwater River from Warner Rapids to Methy Portage at the start of our 1986 trip.In those first days, Gene-an old canoe hand by our standards-gave us much needed advice on when to run rapids and when to walk around them.Both Gene and Wendy did more than their share of camp chores while we examined and photographed rapids and portages.Thanks, too, to Patsi Walton, now of Montreal, who was with us for the last third of our 1986 trip-the distance from Otter Rapids to Cumberland House.Patsi shared her knowledge of northern Saskatchewan's plants and showed us the ones we could safely add to our menu.Patsi also used her guitar, voice, and good humour to enliven our journey.In the years since 1986, several canoeists have supported us on forays to revisit the route.Without exception, they have been endlessly patient during detours made to check and recheck information.They have also freely done more than their share of portaging and camp chores to allow us to pursue small explorations.These canoeists include
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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 | 0.007 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.391 | 0.257 |
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".