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Record W2038993108 · doi:10.3322/canjclin.54.6.295

The Staging of Colorectal Cancer: 2004 and Beyond

2004· review· en· W2038993108 on OpenAlexaff
Carolyn C. Compton, Frederick L. Greene

Bibliographic record

VenueCA A Cancer Journal for Clinicians · 2004
Typereview
Languageen
FieldMedicine
TopicColorectal Cancer Surgical Treatments
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineColorectal cancerStaging systemDistant metastasisStage (stratigraphy)CancerOncologyTNM staging systemNeoplasm stagingMetastasisIntensive care medicineMedical physicsInternal medicine

Abstract

fetched live from OpenAlex

Stage is the strongest predictor of survival for patients with colorectal cancer. Accurate staging also is critical for appropriate patient management and meaningful clinical research. Uniform staging criteria applied in a uniform manner are essential for accurate evaluation of therapies and outcomes. Historically, numerous different staging systems for colorectal cancer have been employed, but a single internationally recognized system is required to ensure a common language for cancer that is understood by clinicians in all specialties. For the tumor, node, metastasis system to remain relevant, it has to continuously undergo critical evaluation and change when clinically indicated.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.071
GPT teacher head0.450
Teacher spread0.378 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations460
Published2004
Admission routes1
Has abstractyes

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