Weather records for the Guelph Turfgrass Institute, Guelph, Ontario [Canada]: Meteorological data 2003 to 2007
Bibliographic record
Abstract
The Agricultural and Forest Meteorology Group, School of Environmental Sciences, University of Guelph, in cooperation with Environment Canada, maintains an automatic weather station at the Guelph Turfgrass Institute located in Guelph, Ontario. This station collects hourly climatic data including air temperature, relative humidity, wind direction and speed, solar radiation, net radiation, precipitation, and soil temperature. This data set includes climatic data collected from 2003 to 2007. The 2003 to 2005 data is presented as annual data files broken down into six categories: hourly data, 0800 data (maximum/minimum values for data collected from 1600 yesterday to 0800 today), 1600 data (maximum/minimum values for data collected from 0800 today to 1600 today), at 2400 hours (maximum/minimum values for data collected at hour 2400), precipitation (every minute of occurrence), and short circuit data (number of times the short circuit voltage is above a set level of 0.100 Volts). Starting in 2006, a different set of variables were collected. The 2006 and 2007 data is presented as annual files broken down into three categories: daily diagnostic data, hourly data, and precipitation data. Supplement data is also available; the weather station supplement data were collected by hand.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.011 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.013 |
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".