Enfermería Integrada en la Escuela
Bibliographic record
Abstract
Manuales Docentes Colección Maestría en Enfermería Escolar Volumen 1. Enfermería integrada en la escuela Departamento de Enfermería. Universidad de Las Palmas de Gran Canaria Como citar esta publicación: APA: Morales-Robaina, S., Medina-Castellano, CD y Montesdeoca-Ramírez, DC (2025). Enfermería integrada en la escuela. Manuales Docentes, vol. 1. Colección Maestría en Enfermería Escolar (MM Marrero-Montelongo, GJ Estévez-Guerra, MJ Morales-Gázquez y DC Montesdeoca-Ramírez, Eds.). Departamento de Enfermería, Universidad de Las Palmas de Gran Canaria. https://doi.org/10.5281/zenodo.14831634 Vancouver: Morales-Robaina S, Medina-Castellano CD, Montesdeoca-Ramírez DC. Enfermería integrada en la escuela. Manuales Docentes. vol. 1. Colección Maestría en Enfermería Escolar. Marrero-Montelongo MM, Estévez-Guerra GJ, Morales-Gázquez MJ, Montesdeoca-Ramírez DC, editores. Las Palmas de Gran Canaria: Departamento de Enfermería, Universidad de Las Palmas de Gran Canaria; 2025. https://doi.org/10.5281/zenodo.14831634 © del texto: Carmen Delia Medina Castellano Daniela Celia Montesdeoca Ramírez Silvia Morales Robaina © de la edición: Editores: María Magdalena Marrero Montelongo Gabriel Jesús Estévez Guerra María José Morales Gázquez Daniela Celia Montesdeoca Ramírez Departamento de Enfermería. Universidad de Las Palmas de Gran Canaria Primera edición digital, 2022 Segunda edición digital, 2025 ISBN: 978-84-09-69597-3
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.067 | 0.040 |
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".