The pulse of driftwood export from a very large forested river basin over multiple time scales, Slave River, Canada
Bibliographic record
Abstract
Abstract This study presents a case study of large wood transport on the great Slave River in northern Canada with the objective to better understand the processes of and variability in pulsed wood fluxes from large forested catchments. We use a varied approach, integrating field characterization of wood, historical anecdotes, repeat aerial imagery of stored wood, and time‐lapse imagery of moving wood, for a robust analysis and synthesis of processes behind pulsed wood flux, from yearly uncongested export to rare congested wood floods. Repeat monitoring of known sites of temporary storage with new or historic imagery proved to be a very useful tool for constraining wood flux histories. Pulsed wood export on the Slave River is not an artifact of episodic recruitment from major up‐basin disturbances, but rather reflects decadal‐ to half‐century‐scale discharge patterns that redistribute wood recruited from channel migration and bank slumping. We suggest that the multiyear flow history is of paramount importance for estimating wood flux magnitude, followed in declining importance by the yearly sequence of peaks and the magnitude and characteristics of the rising limb of individual floods.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".