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Record W3082421635 · doi:10.1097/iae.0000000000002938

Shovel and Cut Technique: Beveled Vitrectomy Probes to Address Diabetic Tractional Retinal Detachments

2020· article· en· W3082421635 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

VenueRetina · 2020
Typearticle
Languageen
FieldMedicine
TopicRetinal and Macular Surgery
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsBevelShovelVitrectomyBevel gearBiomedical engineeringMaterials scienceComputer scienceMedicineOphthalmologyEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

PURPOSE: To describe a surgical technique using the structural advantages of beveled tip cutters. METHODS: The introduction of beveled tips has been one of the few modifications that have been performed to vitrectomy probes since first described by Machemer in 1972. Shovel and cut technique uses this incredible modification to access tighter planes and remove broad diabetic membranes. DESCRIPTION OF TECHNIQUE: The shovel and cut technique can be used with any gauge probe to which the bevel tip is applied. The beveled tip of the cutter is used in a shovel manner to create a tissue plane between the diabetic plaque and the retina. As the beveled tip of the cutter moves parallel to the underlying retina, scar tissue naturally feeds into the cutting port where it is cut and aspirated with low flow rates. CONCLUSION: Shovel and cut technique takes advantage of beveled tip technological innovation to allow easy access and tissue dissection of the most difficult plaques in diabetic membranes. This technique allows us to remove these plaques in a safer, more controlled manner than previous described techniques.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.295
Threshold uncertainty score0.676

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.024
GPT teacher head0.286
Teacher spread0.261 · 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