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End-stage achalasia

2010· review· en· W1917752003 on OpenAlexaff
André Duranceau, Moïshe Liberman, Jocelyne Martin, Pietro Ferraro

Bibliographic record

VenueDiseases of the Esophagus · 2010
Typereview
Languageen
FieldMedicine
TopicGastroesophageal reflux and treatments
Canadian institutionsUniversité de MontréalCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsAchalasiaMedicineMyotomyEsophagectomyContext (archaeology)EsophagusHeller myotomySurgeryStage (stratigraphy)Esophageal sphincterResectionGeneral surgeryEsophageal cancerInternal medicineDiseaseRefluxCancer

Abstract

fetched live from OpenAlex

Despite symptom improvement offered to achalasia patients by either pneumatic dilation or surgical myotomy, 10% to 15% of those so treated will present progressive deterioration of their esophageal function and up to 5% may eventually require an esophagectomy. The natural evolution of achalasia to its end stage as well as the timing of esophagectomy in these patients form the basis of this review. The optimal reconstruction for the decompensated resected esophagus will also be explored: gastric interposition, colon interposition, and jejunal interposition all have their respective advantages and disadvantages. Their use is examined in the exclusive context of resection for achalasia.

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: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

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 science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.028
GPT teacher head0.347
Teacher spread0.319 · 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

Citations83
Published2010
Admission routes1
Has abstractyes

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