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Record W2044919941 · doi:10.1055/s-2005-916284

Follow-Up Recommendations for Colon Cancer

2005· article· en· W2044919941 on OpenAlexaff
W. Donald Buie, Jo-Anne P. Attard

Bibliographic record

VenueClinics in Colon and Rectal Surgery · 2005
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Screening and Detection
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineCarcinoembryonic antigenColorectal cancerRegimenRisk stratificationRandomized controlled trialQuality of life (healthcare)Intensive care medicineOverall survivalOncologyCancerInternal medicineSurgery

Abstract

fetched live from OpenAlex

Recent evidence suggests that intensive follow-up after curative resection of colorectal cancer is associated with a small but significant improvement in survival. Regimens that employ cross-sectional imaging and carcinoembryonic antigen determination appear to have the greatest benefit. A risk-adapted approach to follow-up, intensively following patients at highest risk of recurrence, increases efficacy and cost-effectiveness. Ongoing improvements in risk stratification, disease detection, and treatment will increase the benefits of postoperative surveillance. Large randomized controlled trials are needed to determine the optimal surveillance regimen and must include an analysis of survival, quality of life, and cost-effectiveness to assess efficacy properly.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.907
Threshold uncertainty score0.396

Codex and Gemma teacher scores by category

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

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 head0.083
GPT teacher head0.384
Teacher spread0.301 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations25
Published2005
Admission routes1
Has abstractyes

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