Bibliographic record
Abstract
The abundant spring run-off in Southern Québec is a result of the heavy winter precipitation and the length of the retaining period. One half of the annual discharge occurs in March, April and May, yet the maximum monthly coefficient (April) on the Saint-François is little more than 300. This low figure is due to the length of the thawing season, which extends the flood over at least four weeks, and to the retaining action of the numerous lakes. Occasionally a heavy spring rainfall may alter the character of the run-off, but even then there is never any question of spring flood damage to land or property — the river s are swollen rather than in flood. Critical conditions can arise however on the Saint-François following storm rains and rapid run-off (impermeability and steep slopes). The water rises rapidly, but the fall extends over a week. These floods are more severe than in spring, but damage is still minimal, the lakes in fact store 50% of the surface run-off and in the case of certain tributaries, 75%. Furthermore, the maximum specific discharge is not more than 20 cu. ft/sec/sq. m. for the regulated tributaries (Magog, Massawippï) compared with 80 or more for those that are not. Through the regulating influence of the main tributaries and that of the hydro-electric power dams on the Saint-François itself], the regime of the river is one of the most serene in Southern Québec.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.002 |
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".