IMPROVING THE DEVELOPMENT OF SMALLHOLDER COCOA PLANTATIONS IN PADANG PARIAMAN DISTRICT
Bibliographic record
Abstract
Padang Pariaman is one of three regions in West Sumatra designated as a Cocoa Commodity Agricultural Development Area, along with Pasaman Regency and West Pasaman Regency (Kementan RI, 2018). As stated in the Strategic Plan of the Padang Pariaman Regency Agriculture and Food Security Service for 2021-2026, cocoa is one of the leading commodities in the plantation subsector which is a mainstay for Padang Pariaman Regency as a driver of the community's economy. Data from the last few years shows that the area of smallholder cocoa plantations in Padang Pariaman Regency continues to decline (BPS Padang Pariaman, 2024). The decline in cocoa area and production in Padang Pariaman Regency was caused by the lack of management of cocoa plantations by farmers, resulting in attacks by Plant Pest Organisms (OPT) on cocoa plants, one of which was the Phytophthora palmivora fungus (Nasir, 2016). Policy recommendations that can be implemented by the Department of Agriculture and Food Security of Padang Pariaman Regency in an effort to increase the development of smallholder cocoa plantations include; 1). Determine a direction map for increasing the development of smallholder cocoa plantations in Padang Pariaman Regency based on land suitability classes for cocoa plants, and 2). Establish policy guidelines for the use of certified superior seeds for the rehabilitation and rejuvenation of people's cocoa plantations in Padang Pariaman Regency.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".