Canned Pineapple in Syrup from Thailand Export by using Panel ARDL Method
Bibliographic record
Abstract
This study will shows the impact factor affecting Thailand canned pineapple in syrup export by using model from the assumption of import demand side following Smith (2004). The data from various source i.e. International Financial Statistic by IMF, World Bank database, Bank of Thailand and Office of the Permanent Secretary Ministry of Commerce of Thailand. The research question intended to examine how the relationship between export of pineapple in syrup, and Gross Domestic Product of Importer countries (GDP), Exchange Rate between baht per currency of importer countries and Number of population of importer countries (POP) could be found. From 4 countries such as United State, Japan, Germany, and Canada as well as Japan has a fastest adjusting from short-run equilibrium to long-run equilibrium by have a value closest to zero; error-correction model is -1.8280. Mostly of export canned pineapple has a negative relationship with variables GDP and population both in long-run and short-run equilibrium, means canned pineapple in syrup is possibly substitution goods for those countries,
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".