Análisis del Comportamiento en las Exportaciones de la Pitahaya Ecuatoriana
Bibliographic record
Abstract
The present research consists of the evolutionary analysis of Ecuadorian pitahaya exports from 2019 to 2023, period in which it was intervened to demonstrate the variations in exports of this fruit, its significant contribution to exports in the non-oil category of the country. This fruit, known as exotic, is in great demand and welcomed by international markets thanks to its distinguishing quality. The methodology applied in this research has a quantitative approach, bibliographic and documentary review, in addition to an evaluation of data through sources especially generated by BCE, MAGAP, Agrocalidad, which were used for the development of the study. The analyzed results determined that there is a growth of 40.52% in the periods of study with an expansion in exports, especially in the United States, Canada, China and Hong Kong, which are the main destinations of Ecuadorian pitahaya. In addition, a high level correlation could be found in the quantitative variables; year of export, net weight in exports and the price of pitahaya as FOB merchandise, which have a high significance according to Pearson's scale.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".