Insuficiencias en proyectos de investigación de residentes de Estomatología General Integral: alerta necesaria
Bibliographic record
Abstract
Background: residents' thesis projects represent one of the fundamental activities in their scientific development.Objective: to describe the main difficulties found in the research projects of Comprehensive General dentistry residents.Methods: a retrospective descriptive observational study was carried out at Sagua la Grande Faculty of Medical Sciences from 2014 to 2022. Theoretical and empirical methods were used to support the research and collect information. A model was created for data collection extracted from the projects, and a database was created for its storage.Results: the main difficulties found were: not adequately supporting the research, difficulties in writing the scientific problem, specifically in the relationship between the problem and the type of research, the conceptualization and/or operationalization of the variables, the selection and preparation of the methods, techniques and instruments for collecting information and delimiting the bibliography according to Vancouver standards.Conclusions: the main difficulties were confirmed in the research projects of the residents of Comprehensive General Dentistry due to the need for them to develop research skills from the first year of training, for better professional performance, based on the application of the scientific method in the solution to oral health problems that arise in everyday life.
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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 | 0.014 | 0.087 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".