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Record W4223486139 · doi:10.1080/09273948.2022.2060263

Presence of Panel-reactive Antibodies after Penetrating Keratoplasty

2022· article· en· W4223486139 on OpenAlexaff
Albert Y. Cheung, Joseph H. Jeffrey, Khaliq Kurji, Matthew R. Denny, Amit Govil, Edward J. Holland

Bibliographic record

VenueOcular Immunology and Inflammation · 2022
Typearticle
Languageen
FieldMedicine
TopicCorneal Surgery and Treatments
Canadian institutionsUniversity of Alberta
FundersEye Bank Association of America
KeywordsMedicinePanel reactive antibodyIncidence (geometry)TransplantationSurgeryAntibodyRetrospective cohort studyInternal medicineGastroenterologyOphthalmologyUrologyImmunology

Abstract

fetched live from OpenAlex

PURPOSE: To evaluate the relationship between penetrating keratoplasty (PK) and postoperative PRA level and number of unacceptable antigens. METHODS: A cross-sectionalstudy was performed on patients with history of PK. Patients with prior solid organ transplantation, pregnancy, or blood transfusion were excluded. These findings were combined with a retrospective review. Patients were grouped by single or multiple PKs. The primary outcome was postoperative PRA level. RESULTS: Incidence of postoperative PRA elevation and mean peak PRA was higher in the multiple PK group (p = .08 and p = .010, respectively). Mean number of unacceptable antigens was elevated in the multiple PK group (p = .024). There was a moderately positive correlation between number of PK grafts and PRA level (r = 0.629, p = .0002). CONCLUSIONS: : PK: penetrating keratoplasty; PRA: panel reactive antibodies; OSST: ocular surface stem cell transplantation; LSCD: limbal stem cell deficiency.

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)0.000
metaresearch head score (Gemma)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.233
Teacher spread0.221 · 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

Citations4
Published2022
Admission routes1
Has abstractyes

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