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Record W4213219391 · doi:10.35753/rchsi.v5i4.236

Câncer da Vesícula Biliar - Relato de Casos

2022· article· pt· W4213219391 on OpenAlexaff
Marcos Dantas Moraes Freire, Luís Fernando Pinto Johnson, Mateus Dantas Moraes Freire, Maria Luiza Silva Casé, Lucas Torres Pires, André Luís de Godoy, André Ney Menezes Freire

Bibliographic record

VenueRevista Científica Hospital Santa Izabel · 2022
Typearticle
Languagept
FieldMedicine
TopicCholangiocarcinoma and Gallbladder Cancer Studies
Canadian institutionsAlberta University of the Arts
Fundersnot available
KeywordsMedicineGynecologyGastroenterology

Abstract

fetched live from OpenAlex

O câncer da vesícula biliar é uma doença que representa um grande desafio para médicos clínicos e cirurgiões, por possuir características especiais: alta capacidade de disseminação, invasão por contiguidade e continuidade, crescimento rápido e agressivo, além de apresentação clínica insidiosa, geralmente apresentando sintomas quando o quadro já está avançado. Apresentamos dois casos com desfechos completamente diferentes: um do Hospital Santa Izabel e outro do hospital especializado em câncer A.C. Camargo de São Paulo. Discutimos ainda o tratamento atual e as possíveis intervenções que podem ser traçadas no futuro para o aprimoramento no diagnóstico e na terapêutica dessa grave doença.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.265
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.018
GPT teacher head0.271
Teacher spread0.253 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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
Published2022
Admission routes1
Has abstractyes

Explore more

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