Addressing the key gaps of vineyard cover cropping research: best practices for adaptation to climate change - A systematic review protocol
Bibliographic record
Abstract
A review protocol for the review undertaken as part of the Organic Cluster 3 project. This review will have two primary objectives. The first objective is to review the current literature to assess the roles of cover crops in vineyards (taking into consideration current reviews). The second objective is to assess the degree of efficacy of cover crops in the mitigation and adaptation of vineyards in the context of climate change. Our search will be limited to existing primary, quantitative literature (i.e., field experiments). This review methodology will follow the protocols and steps set forth by Page et al. (2021) in conjunction with the PRISMA Extension for Scoping Reviews (Ticco et al., 2018).
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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 | 0.094 | 0.149 |
| Meta-epidemiology (narrow) | 0.003 | 0.004 |
| Meta-epidemiology (broad) | 0.010 | 0.010 |
| Bibliometrics | 0.019 | 0.016 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.103 | 0.016 |
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".