Bibliographic record
Abstract
These are convulsive and uncertain times, which we have had to live in this quarter of a century and worldwide. Specifically with the rise of the COVID-19 pandemic, which seems to have no end, given that just when we are taking a breath, it threatens us with a new wave that destabilizes our ways of being, feeling, acting and living together as social beings.In the field of education, universities have had to reinvent themselves and work alongside the march of events, with all these vicissitudes. The Universidad Tecnológica del Cibao Oriental, UTECO, is pleased to put into circulation the 11th edition of its Scientific Journal El Capacho, which is available to its readers and research lovers. In this sense, invites you to dive into the topics selected for this issue # 11 of the scientific magazine El Capacho, which is an organ of dissemination of current scientific and educational topics, with the aim of contributing to the educational, scientific and cultural development of the province Sanchez Ramirez, the region, the country and internationally. The topics selected for our avid readers will contribute to their general information, to be nourished, and/or to establish convergences and divergences of the knowledge expressed by their authors.
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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 | 0.002 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.175 | 0.110 |
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".