Appendix A. Tables showing climatic factors influencing the INDVI in May, the maximum NDVI increase and the average slope of NDVI between early May and early July in three study sites in Alberta, climatic factors influencing the INDVI in May, the maximum NDVI increase, and the average slope in NDVI between early May and early July, and correlation coefficients between climatic variables for the GPNP (Italy); and model selection procedures. Also included are figures showing interannual...
Bibliographic record
Abstract
Tables showing climatic factors influencing the INDVI in May, the maximum NDVI increase and the average slope of NDVI between early May and early July in three study sites in Alberta, climatic factors influencing the INDVI in May, the maximum NDVI increase, and the average slope in NDVI between early May and early July, and correlation coefficients between climatic variables for the GPNP (Italy); and model selection procedures. Also included are figures showing interannual variations in NDVI during the study periods and maximum increase in NDVI from 1982 to 2004 in four study sites in Alberta and Italy.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.189 | 0.065 |
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".