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Record W2143524529 · doi:10.1111/nyas.12530

Infection and esophageal cancer

2014· article· en· W2143524529 on OpenAlexaff
Sahar Al‐Haddad, Hala El‐Zimaity, Sara Hafezi‐Bakhtiari, Shanmugarajah Rajendra, Catherine Streutker, Rajkumar Vajpeyi, Bin Wang

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2014
Typearticle
Languageen
FieldMedicine
TopicEsophageal Cancer Research and Treatment
Canadian institutionsUniversity of TorontoToronto General HospitalSt. Michael's Hospital
Fundersnot available
KeywordsEsophageal cancerMedicineEsophagusHuman papilloma virusAdenocarcinomaCancerCarcinomaDiseaseIncidence (geometry)GastroenterologyInternal medicineCancer researchCervical cancer

Abstract

fetched live from OpenAlex

The following, from the 12th OESO World Conference: Cancers of the Esophagus, includes commentaries on infection and cancer, and includes commentaries on the influence of bacterial infections on mucin expression and cancer risk; the role of esophageal bacterial biota in the incidence of esophageal disease; the association between human papilloma virus (HPV) and esophageal squamous cell carcinoma; the role of HPV in esophageal adenocarcinoma; the role of Helicobacter pylori in cardiac carcinoma; and the role of Epstein-Barr virus infection in esophageal cancer.

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)0.005
metaresearch head score (Gemma)0.026
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: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.026
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.003
Science and technology studies0.0020.002
Scholarly communication0.0030.004
Open science0.0030.003
Research integrity0.0240.018
Insufficient payload (model declined to judge)0.0170.006

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 head0.099
GPT teacher head0.403
Teacher spread0.304 · 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

Citations39
Published2014
Admission routes1
Has abstractyes

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