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Individual and combined confrontation visual field tests performed poorly as a screen for visual field abnormalities

2010· letter· en· W2024904622 on OpenAlexaffabout
Barbara S. Connolly, Wieslaw Oczkowski

Bibliographic record

VenueAnnals of Internal Medicine · 2010
Typeletter
Languageen
FieldMedicine
TopicRetinal Imaging and Analysis
Canadian institutionsMcMaster University
Fundersnot available
KeywordsVisual fieldMedicineOphthalmology

Abstract

fetched live from OpenAlex

ACP Journal Club19 October 2010Individual and combined confrontation visual field tests performed poorly as a screen for visual field abnormalitiesBarbara Connolly, MD, Wieslaw Oczkowski, MDBarbara Connolly, MDMcMaster University, Hamilton, Ontario, Canada (B.C., W.O.), Wieslaw Oczkowski, MDMcMaster University, Hamilton, Ontario, Canada (B.C., W.O.)Author, Article, and Disclosure Informationhttps://doi.org/10.7326/0003-4819-153-8-201010190-02011 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail Source CitationKerr NM, Chew SS, Eady EK, Gamble GD, Danesh-Meyer HV. Diagnostic accuracy of confrontation visual field tests. Neurology. 2010;74:1184-90. https://pubmed.ncbi.nlm.nih.gov/20385890Clinical Impact RatingsGIM/FP/GP: Emergency Med: Hospitalists: Neurology: References1 Trobe JD, Acosta PC, Krischer JP, Trick GL. Confrontation visual field techniques in the detection of anterior visual pathway lesions. Ann Neurol. 1981;10:28-34. [PMID: 7271230] Google Scholar2 Johnson LN, Baloh FG. The accuracy of confrontation visual field test in comparison with automated perimetry. J Natl Med Assoc. 1991;83:895-8. [PMID: 1800764] Google Scholar3 Pandit RJ, Gales K, Griffiths PG. Effectiveness of testing visual fields by confrontation [Letter]. Lancet. 2001;358:1339-40. [PMID: 11684217] Google Scholar4 Anderson NE, Mason DF, Fink JN, et al. Detection of focal cerebral hemisphere lesions using the neurological examination. J Neurol Neurosurg Psychiatry. 2005;76:545-9. [PMID: 15774443] Google Scholar Author, Article, and Disclosure InformationAffiliations: McMaster University, Hamilton, Ontario, Canada (B.C., W.O.)This article was published at Annals.org on 5 October 2010. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetails Metrics Cited by11 Neurologisch onderzoek 19 October 2010Volume 153, Issue 8Page: JC4-11KeywordsComputersGlaucomaHospitalistsLesionsNeurologyOptic nervePrimary careSpecificityVisual acuity ePublished: 19 October 2010 Issue Published: 19 October 2010 Copyright & PermissionsCopyright © 2010 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...

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 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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.267
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.387
Teacher spread0.348 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreCommentary

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

Citations3
Published2010
Admission routes2
Has abstractyes

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