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Smoking and cancer of the oesophagus

2010· book-chapter· en· W2493163438 on OpenAlexaboutno aff
Eva Negri

Bibliographic record

VenueOxford University Press eBooks · 2010
Typebook-chapter
Languageen
FieldMedicine
TopicEsophageal Cancer Research and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsIncidence (geometry)MedicineBasal cellCancerAdenocarcinomaCancer incidenceDemographyInternal medicine

Abstract

fetched live from OpenAlex

This chapter reviews studies on the link between smoking and cancer of the oesophagus. In 2002, it was estimated that there were 315,000 new cases of oesophageal cancer (OC) among men and 145,000 among women worldwide. The two major histologic types are squamous cell carcinoma of the oesophagus (SCCO) and adenocarcinoma of the oesophagus (ACO), which account for over 90% of OC. The vast majority of OC are SCCO. Over recent periods, however, a levelling off or decreases in SCCO incidence rates, and increases in ACO incidence rates have been observed in the United States, Canada, and several European countries, especially Northern European ones, and in a few other areas.

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)0.000
metaresearch head score (Gemma)0.000
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: Other · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0180.009

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 head0.027
GPT teacher head0.255
Teacher spread0.228 · 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
GenreOther

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
Published2010
Admission routes1
Has abstractyes

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