Forestry Research Applications Spatial models of Canada- and North America-wide 1971/2000
Bibliographic record
Abstract
This note briefly reports on the development of spatial models of Canada-and North America-wide 1971/2000 30-year mean monthly minimum and maximum temperature, total precipitation and several derived bioclimatic variables. We report on the quality of the models via the interpretation of model accessed over the internet and examined. Canadian applications of ANUSPLIN that have been documented previously include Mackey et al. (1996), Price et al. (2000, 2004), and McKenney et al. (2001, 2004, 2005). Several other applications are currently being written up, including historical monthly models from 1901, extreme minimum temperature models for plant hardiness and weekly models. Methods Numerous peer-reviewed articles on ANUSPLIN document the underlying mathematics. These citations and other relevant literature can be found at the web sites noted above. ANUSPLIN is a multi-variate non-parametric surface fitting approach to developing spatially continuous climate models. It makes use of thin plate-smoothing splines, which are a true multi-variate generalization of univariate splines, as described by Wahba (1990). They should not be confused with simple constructions based on cubic polynomials. Earliest applications were described by Whaba and Wendelberger (1980) but the methodology has been further developed and made operational as a climate mapping tool by Professor Michael Hutchinson at the ANU over the last 20 years or so.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".