Microaprendizaje para estudiar bioeconomía y economía circular en sistemas agroalimentarios - [Microlearning to study bioeconomy and circular economy in agri-food systems]
Bibliographic record
Abstract
La bioeconomía y la economía circular son aspectos novedosos que están despertando un creciente interés. A pesar de ello, existen escasos materiales didácticos relacionados con estos conceptos, especialmente en el ámbito agroalimentario. El proyecto BIOCIR (Aprendizaje activo en bioeconomía y economía circular en sistemas agroalimentarios) pretende suplir esa carencia creando contenido audiovisual mediante técnicas microlearning. El proyecto involucra a alumnos de Grado y Máster de 9 asignaturas de la Escuela Técnica Superior de Ingeniería Agronómica, Alimentaria y de Biosistemas (ETSIAAB) en la elaboración vídeos cortos (2-5 minutos) sobre bioeconomía agraria y economía circular con el objetivo de consolidar una nueva fuente de material didáctico atractivo y transversal. Mediante encuestas a alumnos y profesores se evalúan las competencias adquiridas y la utilidad del material didáctico creado. Blanco-Gutiérrez, Irene; Gutiérrez, Alberto; Ferrer, Juan Ramón; López, Carmen; Soriano, Bárbara; Blanco, María; Arce, Augusto; García; Almendros; Hernández, Carlos Gregorio; Bardají, Isabel; Esteve, Paloma
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".