The Canadian Hiker's and Backpacker's Handbook: Your How-to Guide for Hitting the Trails, Coast to Coast to Coast
Bibliographic record
Abstract
Backcountry hiking in Canada -- comfortably and safely. The Canadian Hiker's and Backpacker's Handbook explains every aspect of taking a hiking or backpacking trip in the Canadian backcountry. From choosing the best footwear to plotting the best route to preparing for emergencies, Ben Gadd provides expert guidance for enjoying Canada's stunning scenery while being responsibly prepared. The book has valuable information on: * What to wear in all landscapes * What to bring from home to the trail * Getting fit, no matter where you live * Techniques for comfortable walking * Safety guidelines at all levels * First aid and accident response * Special tips for hiking and backpacking with kids and dogs.Once trekkers are prepared for the trails, Gadd provides vital information for the conditions that might be encountered. There is also a unique cross-section of trails coast to coast, from Newfoundland to British Columbia and the northern Yukon.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.123 | 0.055 |
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".