La Medicina Natural y Tradicional en los residentes de Pediatría
Bibliographic record
Abstract
Background: Herbal and folk Medicine is a medical specialty that uses methods of health promotion, disease prevention, diagnosis, treatment and rehabilitation. Its adequate knowledge by Pediatric residents allows a high degree of professional development and comprehensive patient care.Objective: to characterize the level of knowledge about Herbal and folk Medicine of Pediatrics residents according to modalities and conditions.Methods: an observational, descriptive and cross-sectional study was carried out in the teaching-care centers “Juan de la Cruz Martínez Maceira” Hospital and“Antonio María Béguez César” pediatric Hospital in the province of Santiago de Cuba, in the first quarter of 2023. Theoretical methods were used: analysis-synthesis and inductive-deductive; empirical ones: questionnaire; and mathematical-statistical for data analysis.Results: the majority of residents considered they had an average level of preparation regarding Herbal and folk Medicine. Homeopathy, followed by floral therapy, were the most used therapeutic modalities; and the respiratory conditions in which its use is most prescribed to patients.Conclusions: the characterization demonstrated that residents require knowledge and skills to take advantage of the wide range of benefits that this specialty brings them for the promotion, prevention, diagnosis, treatment and rehabilitation of pediatric diseases.
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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 | 0.000 | 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) | 0.001 | 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".