Bibliographic record
Abstract
Historical Climate Data (formerly: The National Climate Data and Information Archive - NCDC) is a web-based resource maintained by Environment and Climate Change Canada and the Meteorological Service of Canada. The site houses a number of statistical and data compilation and viewing tools. From the website, users can access historical climate data for Canadian locations and dates, view climate normals and averages, and climate summaries. A list of Canadian air stations and their meteorological reports and activities is also available, along with rainfall statistics for more than 500 locations across Canada. Users can also download the Canadian daily climate data for 2006/07. In addition, technical documentation is offered for data users to interpret the available data. Other documentation includes a catalogue of Canadian weather reporting stations, a glossary, and a calculation of the 1971 to 2000 climate normals for Canada. This resource carries authority and accuracy because it is maintained by a national government department and service. While the majority of the statistics are historical, the data is up-to-date and contains current and fairly recent climate data. This government resource is intended for an audience that has the ability and knowledge to interpret climatological data
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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.034 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.095 | 0.034 |
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".