10.1016/j.quint.2012.04.003
Bibliographic record
Abstract
En los ultimos anos la automatizacion de los procesos de trabajo en la fabricacion de protesis se ha convertido en algo habitual en muchos laboratorios dentales. Con ella se obtienen unos estandares de calidad industrial que permiten una gestion de la calidad reproducible. Los conjuntos de datos generados se pueden almacenar y en muy poco tiempo es posible confeccionar una restauracion identica. Ademas de mejorar la calidad y la productividad, el metodo de fabricacion CAD/CAM permite sobre todo procesar materiales ceramicos de forma fiable. En estos momentos el interes se centra en el perfeccionamiento de la secuencia de trabajo digital mediante la introduccion de sistemas de toma de datos que permiten digitalizar intrabucalmente la situacion clinica del paciente y ofrecen la posibilidad de seguir aumentando la proporcion de restauraciones generadas por ordenador. Este articulo describe los sistemas disponibles y sus posibilidades en la practica clinica diaria.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.002 |
| Insufficient payload (model declined to judge) | 0.897 | 0.798 |
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".