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Record W3128188926 · doi:10.26443/mjm.v1i1.435

Retinopathy of Prematurity: A Clinical Approach

2020· article· en· W3128188926 on OpenAlexaffvenue
Andrew Chow, David M. Weinstock, Alan R. Berger

Bibliographic record

VenueMcGill Journal of Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicRetinopathy of Prematurity Studies
Canadian institutionsCanada Research ChairsUniversity of Toronto
Fundersnot available
KeywordsRetinopathy of prematurityMedicineChildhood blindnessBlindnessRetinopathyIncidence (geometry)PediatricsRetinal detachmentPathophysiologyRetinal DisorderRetinaOphthalmologyRetinalPregnancyOptometryInternal medicineGestational ageEndocrinology

Abstract

fetched live from OpenAlex

Retinopathy of prematurity (ROP), previously known as retrolental fibroplasia, was first described by Terry in 1942 (1). It is a vasoproliferative disorder that is a leading cause of childhood blindness in the United States, causing 550 new cases of infant blindness each year (2). It occurs principally in premature infants treated with high concentrations of oxygen. There are two phases of ROP: (i) an acute phase in which normal vasculogenesis is interrupted, and (ii) a chronic phase in which vascular membranes proliferate into thevitreous. This proliferation can lead to retinal detachment, scarring of the macula, and significant visual loss (3).This article summarizes the incidence, pathophysiology, and classification of ROP. Current protocols for evaluating and treating ROP, as well as long-term sequelae, are also described.

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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.126
GPT teacher head0.363
Teacher spread0.236 · 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

Citations2
Published2020
Admission routes2
Has abstractyes

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