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ACE2 as a Potential Target for Management of Novel Coronavirus (nCoV- 2019)

2020· review· en· W3114886463 on OpenAlex

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

VenueCurrent Drug Discovery Technologies · 2020
Typereview
Languageen
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsÉcole de Technologie SupérieureUniversité du Québec à Montréal
Fundersnot available
KeywordsContext (archaeology)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Coronavirus disease 2019 (COVID-19)Angiotensin-converting enzyme 2Coronavirus2019-20 coronavirus outbreakDiseasePathogenesisMedicineBetacoronavirusRenin–angiotensin systemIntensive care medicineImmunologyBiologyBioinformaticsVirologyInfectious disease (medical specialty)OutbreakPathologyInternal medicine

Abstract

fetched live from OpenAlex

A novel coronavirus termed nCoV-2019 that caused an epidemic of acute respiratory syndrome in humans was first detected in Wuhan, China, in December 2019. nCoV-2019 resulted in thousands of cases of lethal disease all around the world. Unfortunately, there is no specific treatment yet, so a better understanding of the pathobiology of the disease can be helpful. The renin-angiotensin system and its products have several important physiological actions. On the other hand, this system is involved in the pathogenesis of various diseases. In this context, this review article will briefly discuss insights for understanding the role of the angiotensin-converting enzyme 2 (ACE2) receptor as a potentially attractive target for the nCoV-2019-induced acute respiratory syndrome.

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)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.956
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.003
Research integrity0.0000.001
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 head0.140
GPT teacher head0.491
Teacher spread0.351 · 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