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Record W3081679062 · doi:10.14740/jmc3536

Clinical Course of COVID-19 in Identical Twins

2020· article· en· W3081679062 on OpenAlexvenueno aff
Mishita Goel, Victoria González, Reina Badran, Vesna Tegeltija

Bibliographic record

VenueJournal of Medical Cases · 2020
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDiseaseOutbreakCoronavirus disease 2019 (COVID-19)Diabetes mellitusSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)PediatricsCoronavirusComorbidityObesityIntensive care medicineInternal medicineInfectious disease (medical specialty)Pathology

Abstract

fetched live from OpenAlex

The rapid outbreak of coronavirus disease 19 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has led to infection with variable clinical presentations and a wide clinical spectrum. The disease was first reported in Wuhan, China in 2019 and has rapidly spread worldwide. Despite reports of dynamic changes in disease progression, clinical predictors of disease severity have been difficult to identify. The following case describing identical twins with laboratory confirmed COVID-19 who had very different disease courses. These patients resided in the same home and shared many of the same comorbidities, including type 2 diabetes mellitus, hypertension and morbid obesity. Although twin 1 had higher inflammatory markers, white blood cell (WBC) and an arguably more complicated medical history in comparison to their identical twin, the patient experienced a milder and shorter disease course. This case highlights the need for identifying proper disease markers and predictors early in the clinical course in order to direct future management guidelines and timely treatment.

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 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)0.007
metaresearch head score (Gemma)0.576
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.569
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.576
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.239
GPT teacher head0.578
Teacher spread0.339 · 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 teacher head, not a consensus.

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

Citations3
Published2020
Admission routes1
Has abstractyes

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