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Record W2951777982 · doi:10.21037/hbsn.2019.06.06

An updated scoring system for prediction of survival after resection of colorectal liver metastases: addition of KRAS status as an important risk modifier

2020· letter· en· W2951777982 on OpenAlexaff
Evan Jost, Don Major, Elijah Dixon

Bibliographic record

VenueHepatoBiliary Surgery and Nutrition · 2020
Typeletter
Languageen
FieldMedicine
TopicHepatocellular Carcinoma Treatment and Prognosis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineKRASColorectal cancerResectionOncologyOverall survivalInternal medicineHepatectomyChemotherapySurgeryCancer

Abstract

fetched live from OpenAlex

Colorectal liver metastases (CRLM) were traditionally associated with a very poor prognosis after resection, with some historical series reporting 5-year survival rates as low as 14% for completely resected multiple metastases (1). However, as modern chemotherapy and surgical techniques have evolved, there has been much progress made in improving survival for this unique group of patients, with 5-year survival approaching 55% with R0 resection (2). However, not all CRLM are the same, with very different biological behaviour and ultimately oncologic outcomes in different patients.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.749
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.045
GPT teacher head0.242
Teacher spread0.197 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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