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Record W2342175977 · doi:10.1590/0102-6720201600010003

I BRAZILIAN CONSENSUS ON MULTIMODAL TREATMENT OF COLORECTAL LIVER METASTASES. MODULE 2: APPROACH TO RESECTABLE METASTASES

2016· article· en· W2342175977 on OpenAlexaff
Héber Salvador de Castro Ribeiro, Orlando Jorge Martins Torres, M.C. Marques, Paulo Herman, Antônio Nocchi Kalil, Eduardo de Souza Martins Fernandes, Fábio Ferreira de OLIVEIRA, Leonaldson dos Santos Castro, Rodrigo de Morais Hanriot, Suilane Coelho Ribeiro Oliveira, Marcio Boff, Wilson Luiz da Costa, Roberto de Almeida Gil, Túlio Pfiffer, Fábio F. Makdissi, Manoel de Souza Rocha, Paulo Cézar Galvão do Amaral, Leonardo Atem Gonçalves de Araújo COSTA, T.A. Aloia, Luiz Augusto Carneiro D′Albuquerque, Felipe José Fernández Coimbra

Bibliographic record

VenueABCD Arquivos Brasileiros de Cirurgia Digestiva (São Paulo) · 2016
Typearticle
Languageen
FieldMedicine
TopicHepatocellular Carcinoma Treatment and Prognosis
Canadian institutionsPancreas Centre (Canada)
Fundersnot available
KeywordsMedicineColorectal cancerMultimodal therapyMetastasisClinical PracticeRadiologyOncologyInternal medicineCancerGeneral surgeryFamily medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Liver metastases of colorectal cancer are frequent and potentially fatal event in the evolution of patients. AIM: In the second module of this consensus, management of resectable liver metastases was discussed. METHOD: Concept of synchronous and metachronous metastases was determined, and both scenarius were discussed separately according its prognostic and therapeutic peculiarities. RESULTS: Special attention was given to the missing metastases due to systemic preoperative treatment response, with emphasis in strategies to avoid its reccurrence and how to manage disappeared lesions. CONCLUSION: Were presented validated ressectional strategies, to be taken into account in clinical practice.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.500
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.058
GPT teacher head0.276
Teacher spread0.218 · 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 designObservational
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

Citations12
Published2016
Admission routes1
Has abstractyes

Explore more

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