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Record W2890073192 · doi:10.1111/nyas.13858

Risk factors for esophageal cancer: emphasis on infectious agents

2018· review· en· W2890073192 on OpenAlexaff
Hala El‐Zimaity, Vincenzo Di Pilato, Maria Novella Ringressi, Iva Brčić, Shanmugarajah Rajendra, Rupert Langer, Bastian Dislich, Monika Tripathi, Maha Guindi, Robert H. Riddell

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2018
Typereview
Languageen
FieldMedicine
TopicEosinophilic Esophagitis
Canadian institutionsMount Sinai HospitalBrampton Civic Hospital
Fundersnot available
KeywordsDysplasiaEsophagusEsophageal cancerCarcinogenesisHelicobacter pyloriGastroenterologyMedicineCancer researchCarcinomaInternal medicineBiologyCancerImmunology

Abstract

fetched live from OpenAlex

Risk factors for esophageal cancer include genetic factors (such as tylosis) and infectious agents. A variety of organisms have been implicated in esophageal carcinogenesis, either directly or indirectly. In this review, we explore the normal esophageal flora and how it may be controlled, and also the variety of organisms that may affect esophageal carcinogenesis, either directly or indirectly. The organisms with potential direct effects in squamous cell carcinoma include human papillomavirus (HPV), Epstein-Barr virus, and polyoma viruses. Interestingly, HPV is now implicated in esophageal adenocarcinoma (EAC), not in its initiation but in the development of dysplasia, in which HPV33 in particular has been associated. Indirectly, Helicobacter pylori has been associated with EAC by, initially, causing increased acid secretion that increases acid reflux, and by reducing lower esophageal sphincter pressure, which increases gastroesophageal reflux; the latter increases the risk of Barrett's esophagus, and hence EAC. Conversely, subsequent atrophic gastritis may normalize that risk.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.874
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.206
GPT teacher head0.443
Teacher spread0.238 · 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 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

Citations38
Published2018
Admission routes1
Has abstractyes

Explore more

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