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Record W4385649371 · doi:10.1080/09273948.2023.2238817

Postmortem Ultrastructural Analysis of the Retina from COVID-19 Deceased Patients

2023· article· en· W4385649371 on OpenAlex
Carlla Assis Araújo-Silva, Paula M. Marinho, Allexya Affonso Antunes Marcos, Ana M. C. Branco, Victoria Sakamoto, Mateus Matuoka, Nara Franzin de Moraes, Paulo F. G. M. M. Tierno, Walid Mourad, Heloísa Nascimento, Miguel N. Burnier, Wanderley de Souza, Rubens Belfort Neto

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.

Bibliographic record

VenueOcular Immunology and Inflammation · 2023
Typearticle
Languageen
FieldMedicine
TopicRetinal and Optic Conditions
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineRetinaCoronavirus disease 2019 (COVID-19)PathologyRetinalSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)UltrastructureCoronavirus2019-20 coronavirus outbreakOphthalmologyDiseaseInfectious disease (medical specialty)BiologyOutbreak

Abstract

fetched live from OpenAlex

PURPOSE: COVID-19 (coronavirus disease 2019) is an infectious disease caused by SARS-CoV-2, first reported in 2019 in Wuhan, China. Among the common complications is a pro-inflammatory and hypercoagulative response that compromises the vasculature among various organs. METHODS: In this report, we present the postmortem retinal findings of five patients observed by means of optical microscopy and transmission and scanning electron microscopy techniques. RESULTS: Clinical manifestations such as retinal hemorrhages and exacerbated inflammatory infiltrate, altered ultra structure with swollen mitochondria and pyknotic cells in both layers of the retina were observed in all analyzed eyes. CONCLUSION: Our data point to the fragility of this tissue in cases of severe COVID-19.

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 score0.070
Threshold uncertainty score0.187

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.009
GPT teacher head0.252
Teacher spread0.243 · 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