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Record W3041876901 · doi:10.4236/aid.2020.103008

Practical Guideline for Screening the Patients with SARS-CoV-2 Infection and Persian Gulf Criteria for Diagnosis of COVID-19

2020· article· en· W3041876901 on OpenAlexaff
Iraj Salehi-Abari, Shabnam Khazaeli, Fardin Salehi-Abari, Arian Salehi-Abari

Bibliographic record

VenueAdvances in Infectious Diseases · 2020
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 diagnosis using AI
Canadian institutionsYork University
Fundersnot available
KeywordsMedicineARDSAsymptomaticOutbreakPandemicViral pneumoniaPneumoniaDiseaseThroatAtypical pneumoniaVirologyIntensive care medicineImmunologyCoronavirus disease 2019 (COVID-19)LungInternal medicineInfectious disease (medical specialty)Surgery

Abstract

fetched live from OpenAlex

The new Coronavirus disease or COVID-19 is a contagious viral/immune-logical systemic disorder with predominantly respiratory features caused by human infection with SARS-CoV-2, which is rapidly spreading from person-to-person all around the world as a pandemic. The new outbreak of COVID-19 first appeared in Wuhan, China in December 2019. This virus is transmitted from human to human in various ways including air, aerosol, touching, and fecal-oral ways. The SARS-CoV-2 survives for several days in the environment. The SARS-CoV-2 virus multiplies within the cells of mouth-throat or nose-throat, and despite the production of antibodies by the human immune system, if the virus continues to multiply and progress, it will enter the bloodstream and reach its target organ, the lungs. It takes an incubation period of one to fourteen days for the initial symptoms/signs of disease to appear as fever, dry cough, and fatigue. Finally, shortness of breath due to pneumonia/pneumonitis with or without Acute Respiratory Distress Syndrome (ARDS) causes the patient to be hospitalized and transferred to ICU. Older people with underlying disorders account for the majority of deaths from COVID-19, while children under the age of 15 - 20 are the main carriers of the SARS-CoV-2. About 40% of patients with COVID-19 are asymptomatic and, 40% mild, 15%; severe, and 5% are critical COVID-19. COVID-19 Molecular Diagnostic Tests and COVID-19 Antibody Tests are two types of diagnostic kit tests for identification of the SARS-CoV-2 and the High Resolution Computerised Tomography (HRCT) scanning of lungs is the best imaging method for detecting pneumonia/pneumonitis and assessing its severity. This paper is intended to present a health system called COVID-19 Referral System for screening and developing very sensitive diagnostic criteria as Persian Gulf Criteria for diagnosis of COVID-19. By using these two methods and performing the SARS-CoV-2 kit tests more and more widely, and performing accurate isolation of patients and virus carriers and complete quarantine of red zones, it is possible to successfully control the SARS-CoV-2 epidemics.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.031
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0310.014

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 head0.053
GPT teacher head0.413
Teacher spread0.360 · 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 designNot applicable
Domainnot available
GenreMethods

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

Citations14
Published2020
Admission routes1
Has abstractyes

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