Condition of Plantation and Development Strategy of Sago Garden
Bibliographic record
Abstract
Sago plants in Indonesia have great potential, such as a very large area, a high source of carbohydrates, high productivity, and can be used as various kinds of derivative products. Sago is a local specific food ingredient in Maluku. Especially people in rural areas consume sago as a staple food. This study aims to determine plantations' condition and sago gardens' development strategy in Sumber Agung Village, East Seram Regency, Maluku Province. The research sample is determined by purposive sampling because farmers desire and are willing to organize sago forests into sago gardens. The number of samples is 80 respondents. The results show that the sago garden is located in an area with Alluvial Plain physiography with choppy microrelief so that there are sporadic spreading basins that cause puddles. The height of this garden's location ranges between 25-35 m above sea level, with a slope varying between 0-3%. This microrelief condition results in a puddle of water, but this puddle is temporal, where the pool occurs during the rainy season and sometime after the rainy season. The people of Sumber Agung Village, who are very, welcoming friendly, and open to developing innovations in the management of sago gardens, are important to preserve Sago in the future. The transmigration community in Sumber Agung Village supports the structuring of sago gardens. This is evidence of ethnic diversity, but concern for Sago is grave. This is good because Maluku is famous for local sago food, so sago forests need to be organized into representative and sustainable sago gardens. The community's perception of factors towards the development of sago plantations shows that the convenience construct does not significantly affect the needs construct. While the aesthetics construct, the benefit significantly influences the needs to construct.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 teacher head, 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".