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Record W4307102831 · doi:10.1007/s10633-022-09903-w

Comparing the RETeval® portable ERG device with more traditional tabletop ERG systems in normal subjects and selected retinopathies

2022· article· en· W4307102831 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueDocumenta Ophthalmologica · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinal Development and Disorders
Canadian institutionsMcGill University Health CentreMcGill UniversityMontreal Children's Hospital
FundersCanadian Institutes of Health ResearchMcGill University Health CentreMcGill UniversityInstitut de recherche, Centre universitaire de santé McGill
KeywordsErgOptometryElectroretinographyOphthalmologyMedicineRetinalComputer science

Abstract

fetched live from OpenAlex

Abstract Purpose Our study aimed to determine if ISCEV standard-like ERGs recorded with the LKC RETeval ® portable ERG unit compared to those obtained using the more traditional tabletop unit. Methods ERGs recorded from normal subjects and patients affected with retinal ON and OFF pathway anomalies were compared. Analysis included peak time and amplitude measurements as well as time–frequency domain analysis with the discrete wavelet transform of waveforms obtained with the two systems. Results Although both systems were similarly able to record reliable and highly reproducible ERG responses, there were major discrepancies in ERG responses between the portable and tabletop units, pointing toward a weaker stimulation of the retinal OFF pathway with the portable RETeval ® unit. Conclusion The portable RETeval ® unit appears to be able to record highly reproducible and diagnostically useful clinical ERGs, albeit with some significant differences in waveform composition compared to those obtained with more standard tabletop systems. Given the unknown origin of these waveform discrepancies, if left uncorrected, these differences could potentially lead to erroneous interpretation when used in the clinical context and/or compared to ERGs recorded using more traditional table top units. Clearly, more research is warranted before handheld devices, such as the RETeval ® , can be homologated as a diagnostically sound ERG devices.

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 score0.019
Threshold uncertainty score0.544

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 head0.023
GPT teacher head0.236
Teacher spread0.213 · 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