Bibliographic record
Abstract
Abstract This second edition of the book contains 12 chapters, which aims to: (1) to update existing chapters with the tremendous advances in temperate agroforestry knowledge that have come to light in the last 20 years; and (2) if possible, to add new global regional examples of temperate agroforestry. Several changes have been made to the second edition. North America has been split into separate American (USA) and Canadian chapters as the discipline has advanced greatly in both countries in the time that has passed since the publication of the first edition. Similarly, the UK has been separated from Europe, and both are now presented as separate chapters. Chapters on New Zealand, Australia, China and Argentina have been retained as almost entirely new chapters and additional chapters have been added for temperate India and Chile, bringing the total number of regional temperate agroforestry endeavours to ten. It is hoped that the readers will see and embrace the important role that agroforestry systems in temperate regions can play with respect to mitigating the ecological footprint of modern farming systems.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.004 |
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".