Bibliographic record
Abstract
De Computis presenta su Volumen 14, Número 25 (diciembre, 2016) incluyendo sietetrabajos doctrinales realizados por autores de España, Italia, Canadá, Francia y Portugal, yescritos en español, italiano, inglés y portugués. Esto es una prueba del interés de la revistapor abrirse a su entorno internacional. Los autores de este número han sido Marco A.Marinoni y Andrea Cilloni, (Catholic University of Sacred Heart, Piacenza y University ofParma); Richard Mattessich y Giuseppe Galassi (University of BritishColumbia,Vancouver B.C. y University of Parma), Anne Dubet (Université ClermontAuvergne), Candelaria Castro, Mercedes Calvo y Sonia Granado (Universidad de LasPalmas de Gran Canaria); Manuel Gonçalves (ISCAC - Coimbra Business School);Massimo Costa (Universidad Bocconi de Milán) y Sergio Solbes (Universidad de LasPalmas de Gran Canaria). Agradecemos a los autores el haber confiado en De Computispara la difusión de sus trabajos.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.229 | 0.090 |
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".