An Integrated Approach to the Estimation of Streamflow Drought Quantiles
Bibliographic record
Abstract
Nous avons developpe une methode pour combiner des donnees sur les secheresses hydrologiques, d'une part synthetiques (generees) et d'autre part reconstruites a partir d'informations paleoclimatiques (largeurs des anneaux de croissance d'arbres). Les donnees dendrochronologiques ont ete utilisees pour reconstruire les ecoulements en cours d'eau, pour des periodes ou aucune observation n'en a ete realisee. Les donnees reconstruites ont ensuite ete utilisees comme source de donnees historiques pour l'estimation des quantiles de severite de secheresse. Les donnees generees ont ete obtenues grâce a une methode de re-echantillonnage des plus proches voisins, tandis que la reconstruction des anneaux d'arbres a ete realisee grâce a un modele de regression. La methode a ete appliquee a des donnees de la Riviere Athabasca en Alberta, au Canada. Les resultats montrent l'operationnalite et l'utilite de la methode pour obtenir des estimations des quantiles extremes de severite de secheresse plus exactes et precises.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".