Bibliographic record
Abstract
We had intended to spend our first night on the river in the area of the Hague Ferry crossing, roughly 25 kilometers downstream of the Clarkboro Ferry, where we had launched the canoe and two kayaks in which our party was traveling.However, when we reached the Hague Ferry crossing before noon it took very little discussion to decide that we would push on.Not only was there at least eight hours of daylight left, but also the next day's forecast called for high winds and possibly rain, a combination that can drastically slow the progress of a boat on the river, even if that boat is moving with the current, travelling downstream.We agreed on another hour or two of paddling, maybe 10 or 15 kilometers, but the shifting shorelines, sandbars, and islands that line and dot the South Saskatchewan River left us very little in the way of options for campsites.When we finally pulled the boats from the water onto the sandbar at the place we had originally planned to camp on our second night-roughly 45 kilometers from where we launched that morning-we were tired and hungry and victorious.
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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 | 0.001 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.734 | 0.517 |
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".