Identification of Pineapple Fruit Rot Disease in Kubu Raya, West Borneo
Bibliographic record
Abstract
Pineapple productivity in West Borneo ranks second after bananas. One of the obstacles in pineapple cultivation is the presence of diseases that attack pineapple plantations. Symptoms of pineapple plant disease are an indication that the plant is attacked by pathogens. This study aims to identify pathogens that cause rot symptoms in pineapple fruit. The methods used in this study include surveys, survey evaluations, observation of symptoms in pineapple plantations, and laboratory tests of pathogens that cause pineapple fruit rot disease in Kubu Raya, West Borneo. Sampling was carried out by purposive sampling on pineapples with rot symptoms. Based on the results of the study obtained, it shows that the symptoms of pineapple fruit rot disease are characterized by the presence of soft rot that is blackish brown in color, rotten inside and emits a distinctive odor. Pineapple fruit rot is caused by the pathogens Curvularia sp. and Fusarium sp.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".