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Record W2594005933 · doi:10.1159/000457807

Three-Dimensional Printing of a Transconjunctival Vitrectomy Trocar-Cannula System

2017· article· en· W2594005933 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOphthalmologica · 2017
Typearticle
Languageen
FieldMedicine
TopicRetinal and Macular Surgery
Canadian institutionsQueen's UniversityUniversity of British Columbia
Fundersnot available
KeywordsCannulaVitreoretinal surgeryVitrectomyBiomedical engineeringMedicineSurgery

Abstract

fetched live from OpenAlex

PURPOSE: The aim of this paper was to study the feasibility of manufacturing a customizable trocar-cannula system for vitreoretinal surgery utilizing commercially available three-dimensional (3D) printing technology. METHODS: A digital model of a trocar-cannula system for vitreoretinal surgery was created using computer-aided design (CAD) software and printed utilizing a laser-sintering 3D printer in modified ABS thermoplastic material. The trocar-cannula prototypes were tested in pig eyes. RESULTS: A customizable digital model was created using commercially available CAD software. Three trocar-cannulas were printed. The smallest cannulas that could be printed had dimensions between 21 and 22G. The trocar-cannulas were inserted in pig eyes after performing sclerotomies with a commercially available 20G MVR blade. One cannula broke during insertion. CONCLUSIONS: This study demonstrates the feasibility of printing a transconjunctival vitrectomy trocar-cannula system with commercially available 3D print technology. The 3D printer and build material used resulted in trocar-cannulas with functional limitations including a minimum size achievable and mechanical resistance.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.192
Threshold uncertainty score0.449

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.039
GPT teacher head0.293
Teacher spread0.253 · 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