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Anesthesia modalities for cataract surgery

2000· review· en· W1983147198 on OpenAlexaff
Joel Naor, Allan R. Slomovic

Bibliographic record

VenueCurrent Opinion in Ophthalmology · 2000
Typereview
Languageen
FieldMedicine
TopicIntraocular Surgery and Lenses
Canadian institutionsToronto Western HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineAnesthesiaModalitiesLidocaineCataract surgeryAnestheticTopical anesthesiaTreatment modalitySurgery

Abstract

fetched live from OpenAlex

Research articles on anesthesia modalities for cataract surgery are reviewed. A growing trend toward the use of topical anesthesia is apparent. Particular emphasis in the literature is given to determining the safety and efficacy of various forms of topical anesthesia using injectable anesthesia as a frame of reference. A consensus of opinion points toward the use of topical application of anesthetic drops plus intracameral unpreserved lidocaine 1% as the anesthesia modality that provides the best level of analgesia and comfort to patients while not compromising ocular safety. Several articles reporting complications of injectable anesthesia are also reviewed.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.015
Threshold uncertainty score0.050

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.004
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0150.006

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 head0.261
GPT teacher head0.454
Teacher spread0.192 · 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

Citations53
Published2000
Admission routes1
Has abstractyes

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