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Record W2609579349 · doi:10.1155/2017/8628206

Identification of Abnormal Biliary Anatomy Utilizing Real-Time Near-Infrared Cholangiography: A Report of Two Cases

2017· article· en· W2609579349 on OpenAlexaboutno aff
Joseph D. Bozzay, Diego Vicente, Elliot Jessie, Carlos J. Rodríguez

Bibliographic record

VenueCase Reports in Gastrointestinal Medicine · 2017
Typearticle
Languageen
FieldMedicine
TopicGallbladder and Bile Duct Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCholangiographyLaparoscopic cholecystectomyCholecystectomyRadiologyBiliary drainageIdentification (biology)General surgeryMedical physicsBiology

Abstract

fetched live from OpenAlex

Biliary duct anomalies are commonly encountered during laparoscopic cholecystectomy. Advancements in the field of surgery allow for enhanced intraoperative detection of these abnormalities. Fluorophore injection and near-infrared (NIR) imaging can provide real-time intraoperative anatomic feedback without intraoperative delays and ionizing radiation. This report details two cases where the PINPOINT Endoscopic Fluorescence Imaging System (NOVADAQ, Ontario, Canada) was used to identify anomalies of the biliary tree and guide operative decision-making.

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)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.318
Threshold uncertainty score0.923

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.023
GPT teacher head0.326
Teacher spread0.302 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

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

Citations3
Published2017
Admission routes1
Has abstractyes

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