Bibliographic record
Abstract
Snow accumulation patterns were determined for clearings and adjacent forest at Marmot Creek experimental watershed and James River, Alberta. At maximum accumulation snow water equivalent (SWE) was greater in clearings than in forest whether clearings were large, as in 8- to 13-ha blocks where SWE averaged 20 % more than in the forest, or small as in the 1/4 to 6-H (height) diameter circular clearings where SWE was 13-45 % greater than in the forest. SWE was 42 to 52 % less in north than in south sectors of 2-6 H clearings. These differences increased with clearing size and time since beginning of accumulation period and are caused by snow ablation (melt and evaporation), a function of direct solar radiation reaching the snowl•ack. In such situations the snow that has accumulated on the ground cannot be considered a measure of the snow that has actually fallen there. For water balances and hydrologic modeling, snow measurements in partially cleared watersheds must be adjusted for temporal and spatial factors specific to the watershed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.044 | 0.010 |
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".