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Record W1976663733 · doi:10.1159/000112625

Comparison of the Infiniti Vision and the Series 20,000 Legacy Systems

2008· article· en· W1976663733 on OpenAlexfundno aff
Luis E. Fernández de Castro, Kerry D. Solomon, Daniel Hu, David T. Vroman, Helga P. Sandoval

Bibliographic record

VenueOphthalmologica · 2008
Typearticle
Languageen
FieldMedicine
TopicIntraocular Surgery and Lenses
Canadian institutionsnot available
FundersNational Eye InstituteNational Institutes of HealthAGE-WELLResearch to Prevent Blindness
KeywordsPhacoemulsificationOphthalmologyVisual acuityMedicine

Abstract

fetched live from OpenAlex

PURPOSE: To compare the efficiency of the Infiniti vision system and the Series 20,000 Legacy system phacoemulsification units during routine cataract extraction. METHODS: Thirty-nine eyes of 39 patients were randomized to have their cataract removed using either the Infiniti or the Legacy system, both using the Neosonix handpiece. System settings were standardized. Ultrasound time, amount of balanced salt solution (BSS) used intraoperatively, and postoperative visual acuity at postoperative days 1, 7 and 30 were evaluated. RESULTS: Preoperatively, best corrected visual acuity was significantly worse in the Infiniti group compared to the Legacy group (0.38 +/- 0.23 and 0.21 +/- 0.16, respectively; p = 0.012). The mean phacoemulsification time was 39.6 +/- 22.9 s (range 6.0-102.0) for the Legacy group and 18.3 +/-19.1 s (range 1.0-80.0) for the Infiniti group (p = 0.001). The mean amounts of intraoperative BSS used were 117 +/- 37.7 ml (range 70-195) in the Legacy group and 85.3 +/- 38.9 ml (range 40-200) in the Infiniti group (p = 0.005). No differences in postoperative visual acuity were found. CONCLUSION: The ability to use higher flow rates and vacuum settings with the Infiniti vision system allowed for cataract removal with less phacoemulsification time than when using the Legacy system.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.052
GPT teacher head0.317
Teacher spread0.266 · 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 designObservational
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

Citations2
Published2008
Admission routes1
Has abstractyes

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