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Record W3084763251 · doi:10.1371/journal.pone.0238614

Isolation and characterization of severe acute respiratory syndrome coronavirus 2 in Turkey

2020· article· en· W3084763251 on OpenAlexaboutno aff
Shaikh Terkıs Islam Pavel, Hazel Yetişkin, Günsu Aydın, Can Holyavkin, Muhammet Ali Uygut, Zehra Beştepe Dursun, İ̇lhami Çelik, Ceren Cevik, Aykut Özdarendeli

Bibliographic record

VenuePLoS ONE · 2020
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsnot available
FundersErciyes ÜniversitesiTürkiye Sağlık Enstitüleri Başkanlığı
KeywordsCoronavirusPandemicVero cellVirologyOutbreakCoronavirus disease 2019 (COVID-19)BiologyVirusMedicineDiseaseInfectious disease (medical specialty)Internal medicine

Abstract

fetched live from OpenAlex

Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and associated with severe respiratory illness emerged in Wuhan, China, in late 2019. The virus has been able to spread promptly across all continents in the world. The current pandemic has posed a great threat to public health concern and safety. Currently, there are no specific treatments or licensed vaccines available for COVID-19. We isolated SARS-CoV-2 from the nasopharyngeal sample of a patient in Turkey with confirmed COVID-19. We determined that the Vero E6 and MA-104 cell lines are suitable for supporting SARS-CoV-2 that supports viral replication, development of cytopathic effect (CPE) and subsequent cell death. Phylogenetic analyses of the whole genome sequences showed that the hCoV-19/Turkey/ERAGEM-001/2020 strain clustered with the strains primarily from Australia, Canada, England, Iran and Kuwait and that the cases in the nearby clusters were reported to have travel history to Iran and to share the common unique nucleotide substitutions.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.102
GPT teacher head0.316
Teacher spread0.214 · 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

Citations24
Published2020
Admission routes1
Has abstractyes

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Same venuePLoS ONESame topicSARS-CoV-2 and COVID-19 ResearchFrench-language works237,207