UQAM-Heatwave ERA5 Archive and Temperatures (U-HEAT) Catalog
Bibliographic record
Abstract
The UQAM Heatwave ERA5 Archive and Temperatures (U-HEAT) catalog is a global dataset of temperature and heatwave data spanning 1940 to 2022. The temperature data features the maximum daily 2-m temperature, the 90th percentile of the maximum daily 2-m temperature, and an indication as to whether a given location (grid point) is experiencing a heatwave or not on a given day. The heatwave data includes metrics such as the duration, the cumulated intensity and the maximum intensity of heatwaves occuring in the study period as well as their location (grid point) and start date. Both the temperature and the heatwave metrics data were calculated from the ERA5 data produced by the European Centre for Medium-Range Weather Forecasts (ECMWF). More information on the catalog can be found in the documentation and the README files. Le catalogue UQAM Heatwave ERA5 Archive and Temperatures (U-HEAT) est un jeu de données global de température et de vague de chaleur pour la période entre 1940 et 2022. Les données de température comprennent le maximum quotidien de la température à 2m, le 90e percentile du maximum quotidien de la température à 2m et une indication permettant de savoir si un lieu donné (point de grille) subit ou non une vague de chaleur pour un jour donné. Les données de vague de chaleur incluent des métriques comme la durée, l'intensité cumulée et l'intensité maximale de vagues de chaleur qui se sont produites durant la période d'étude en plus de leur emplacement (point de grille) et leur date de début. Les données de température et de vague de chaleur ont été calculées à partir du jeu de données ERA5 produit par le European Centre for Medium-Range Weather Forecasts (ECMWF). Le fichier de documentation et le fichier README peuvent être consultés pour obtenir plus d'information à propos du catalogue.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.012 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.180 | 0.203 |
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".