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Record W4283448146 · doi:10.46919/archv3n4-003

Síndrome de Behçet – os desafios do diagnóstico

2022· article· pt· W4283448146 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal Archives of Health · 2022
Typearticle
Languagept
FieldMedicine
TopicOcular Diseases and Behçet’s Syndrome
Canadian institutionsCytodiagnostics (Canada)
Fundersnot available
KeywordsMedicineGynecology

Abstract

fetched live from OpenAlex

Introdução: A doença de Behçet (DB) é uma afecção inflamatória multissistêmica de causa ainda desconhecida. Clinicamente apresenta úlceras orais, genitália, uveítes, lesões cutâneas e vasculites recorrentes. Atualmente reconhecida como uma doença autoimune, com fatores genéticos do portador e fatores desencadeantes ambientais. Objetivo: revisar a patologia e descrever os critérios internacionais para o diagnóstico. Método: Relato de um caso clínico que envolveu multidisciplinas para o diagnóstico. Conclusão: Embora não haja alterações laboratoriais ou histopatológicas definidas da doença, o diagnóstico depende de uma avaliação clínica criteriosa que quando são determinantes para o prognóstico.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.407
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0070.000

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 head0.020
GPT teacher head0.307
Teacher spread0.287 · 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