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Record W3185398318 · doi:10.5114/ko.2021.105633

Spectacle correction of anisometropia following cataract surgery

2021· article· en· W3185398318 on OpenAlexaboutno aff
Sławomir Nogaj, Katarzyna Dubas, Andrzej Michalski, Marcin Stopa

Bibliographic record

VenueKlinika Oczna · 2021
Typearticle
Languageen
FieldMedicine
TopicGlaucoma and retinal disorders
Canadian institutionsnot available
Fundersnot available
KeywordsAnisometropiaMedicineSpectacleCataract surgerySurgeryOphthalmologyVisual acuityRefractive error

Abstract

fetched live from OpenAlex

ENWEndNote BIBJabRef, Mendeley RISPapers, Reference Manager, RefWorks, Zotero AMA Nogaj S, Dubas K, Michalski A, Stopa M. Spectacle correction of anisometropia following cataract surgery. Klinika Oczna / Acta Ophthalmologica Polonica. 2021. doi:10.5114/ko.2021.105633. APA Nogaj, S., Dubas, K., Michalski, A., & Stopa, M. (2021). Spectacle correction of anisometropia following cataract surgery. Klinika Oczna / Acta Ophthalmologica Polonica. https://doi.org/10.5114/ko.2021.105633 Chicago Nogaj, Sławomir, Katarzyna Dubas, Andrzej Michalski, and Marcin Stopa. 2021. "Spectacle correction of anisometropia following cataract surgery". Klinika Oczna / Acta Ophthalmologica Polonica. doi:10.5114/ko.2021.105633. Harvard Nogaj, S., Dubas, K., Michalski, A., and Stopa, M. (2021). Spectacle correction of anisometropia following cataract surgery. Klinika Oczna / Acta Ophthalmologica Polonica. https://doi.org/10.5114/ko.2021.105633 MLA Nogaj, Sławomir et al. "Spectacle correction of anisometropia following cataract surgery." Klinika Oczna / Acta Ophthalmologica Polonica, 2021. doi:10.5114/ko.2021.105633. Vancouver Nogaj S, Dubas K, Michalski A, Stopa M. Spectacle correction of anisometropia following cataract surgery. Klinika Oczna / Acta Ophthalmologica Polonica. 2021. doi:10.5114/ko.2021.105633.

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)0.006
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 score0.023
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0230.004

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 head0.015
GPT teacher head0.268
Teacher spread0.253 · 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".

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Citations0
Published2021
Admission routes1
Has abstractyes

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