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Record W1576504112 · doi:10.15381/os.v6i12.3976

DESAFÍOS DE LA INVESTIGACIÓN EN SALUD EN AMÉRICA LATINA. DESAFÍOS DE LA INVESTIGACIÓN EN LAS FACULTADES DE ODONTOLOGÍA.

2003· article· en· W1576504112 on OpenAlexaboutno aff
Víctor Lahoud Salem

Bibliographic record

VenueAmericanae (AECID Library) · 2003
Typearticle
Languageen
FieldHealth Professions
TopicHealth and Medical Education
Canadian institutionsnot available
Fundersnot available
KeywordsDeclarationHealth professionalsPolitical sciencePublic healthWelfare economicsMedicineNursingHealth careLawEconomics

Abstract

fetched live from OpenAlex

Los avances tecnológicos, científicos y la producción de conocimientos en un mundo globalizado, ofrecen a la profesión dental la oportunidad de transformar su práctica clínica y revolucionar la odontología. Igualmente, la Declaración de Toronto sobre la Equidad en Salud (2002) compromete a los profesionales de la salud y a las organizaciones internacionales a reafirmar y promover entre sus miembros, la importancia de la atención primaria en salud y la prevención y el compromiso para rebartir toda decisión de los sectores público y privado, que incremente las inequidades en materia de salud y a aclamar toda decisión encaminada a mejorarla, además a promover la investigación sobre la problemática de la salud bucal.

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 imitation

Not 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.

metaresearch head score (Codex)0.048
metaresearch head score (Gemma)0.057
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.121
Threshold uncertainty score0.254

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0480.057
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0070.008
Science and technology studies0.0050.011
Scholarly communication0.0120.010
Open science0.0020.007
Research integrity0.0070.006
Insufficient payload (model declined to judge)0.0140.002

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.

Opus teacher head0.016
GPT teacher head0.408
Teacher spread0.392 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations0
Published2003
Admission routes1
Has abstractyes

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