MétaCan
Menu
← Back to cohort
Record W3081588394 · doi:10.14740/jmc3566

A Case of COVID-19 Failed in Viral Identification but Showed Consistent Host Responses to Severe Acute Respiratory Syndrome Coronavirus 2

2020· article· en· W3081588394 on OpenAlexvenueno aff
Yoshitaka Maeda, Hiroyuki Miyo, Atsuki Ohashi, Takanobu Yamamoto, Tomoyuki Ogata

Bibliographic record

VenueJournal of Medical Cases · 2020
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCoronavirus disease 2019 (COVID-19)PneumoniaCoronavirusViral pneumoniaFavipiravirSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Mycoplasma pneumoniaeRespiratory systemPrednisoloneAntibodyVirologyImmunologyInternal medicineDiseaseInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

In a 75-year-old hemodialysis patient, pneumonia manifested with computed tomography (CT) images suggestive of coronavirus disease 2019 (COVID-19). Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ribonucleic acid (RNA) was not detected with repeated polymerase chain reaction (PCR) tests, but serum immunoglobulin G (IgG) and IgM antibodies against SARS-CoV-2 turned positive with two different assay kits. The patient was thus treated as a probable COVID-19 case, and then recovered through the intensive care including ciclesonide, favipiravir, and methyl prednisolone. In PCR-negative cases, the diagnosis of COVID-19 cannot be established at present, but such COVID-19 cases certainly exist. To avoid a delay in treatment of COVID-19, available diagnostic tools should be utilized with careful attention for their limitations.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.002
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 head0.182
GPT teacher head0.478
Teacher spread0.296 · 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 designCase report
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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Medical Cases→Same topicCOVID-19 Clinical Research Studies→French-language works237,207→