Pendugaan Permintaan Impor Komoditi Kedele dan Gandum Indonesia
Bibliographic record
Abstract
Soybean and wheat imported by Indonesian government increase steadily in line with its population and welfare growth. The main reason of remarkable increasing demand is the increasing trend of the industries using those commodities as a raw material. The main source of soybean importation is China and USA, on the other hand wheat is mainly imported from Australia, USA, Canada and Argentina in determining the import demand, the AID model and translog functional form are used, but the Armington model is not suggested due to the restricted assumption needed. The result indicated that there is substitution effect for Indonesian soybean import between Asian and non-Asian Countries. For the same commodity, among Asian countries the nature of importation is complement. For wheat there is a tendency that the nature of relationship is substitute among the countries as a source of Indonesia's importation. Soybean import price elasticity ranges between -0.6 to -2.2, and -0.3 to -0.7 for wheat
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".