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Record W3127093808 · doi:10.1093/jscr/rjaa606

Enhanced neuro-ophthalmologic evaluation to support separation of craniopagus twins

2020· article· en· W3127093808 on OpenAlex
Sohaib R. Rufai, Sri Gore, Siân E. Handley, Oliver R. Marmoy, Juling Ong, David Dunaway, Owase Jeelani

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Surgical Case Reports · 2020
Typearticle
Languageen
FieldMedicine
TopicAssisted Reproductive Technology and Twin Pregnancy
Canadian institutionsnot available
FundersNIHR Great Ormond Street Hospital Biomedical Research CentreMedical Research Council CanadaDepartment of Health and Social CareMedical Research CouncilNational Institute for Health and Care Research
KeywordsMedicineConjoined twinsOptometryOphthalmologySurgery

Abstract

fetched live from OpenAlex

Craniopagus conjoined twins are extraordinarily rare and present unique challenges to the multidisciplinary team. There is a paucity of literature on optimizing neuro-ophthalmologic evaluation in craniopagus twins. Herein, we present our enhanced neuro-ophthalmologic evaluation and management in 17-month-old male craniopagus twins, uniquely using handheld optical coherence tomography (OCT) plus portable slit-lamp biomicroscopy, indirect ophthalmoscopy and modified forced-choice preferential looking assessment. Staged surgical separation was supported by enhanced neuro-ophthalmologic evaluation, detailed radiology, three-dimensional printing and virtual reality simulation. This represents the fourth separation of craniopagus twins by our unit.

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.

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)0.002
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: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.479

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.064
GPT teacher head0.370
Teacher spread0.306 · 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