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Record W3018076390 · doi:10.38124/ijisrt20apr398

Hypothesis: Advanced Biotechnological Treatment Approaches Against SARS-CoV-2 (COVID-19)

2020· article· en· W3018076390 on OpenAlexaff
Farmanli Orkhan, Uysal Melike, Ayhan Yunus Emre, Gokdemir Cihan, Donmez Omer Faruk, Bastug Samet, Parlak Murat, Uckun Ilknur, Jafarov Alemdar, Pamuk Ibrahim, Farmanli Kubra, Karatas Ihsan

Bibliographic record

VenueInternational Journal of Innovative Science and Research Technology (IJISRT) · 2020
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsArtificial Intelligence in Medicine (Canada)
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)PandemicSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Coronavirus2019-20 coronavirus outbreakIntensive care medicineVirologyDiseaseMedicineDrugInfectious disease (medical specialty)PharmacologyInternal medicineOutbreak

Abstract

fetched live from OpenAlex

The new type of coronavirus, called COVID19, which began to spread all over the world, caused a pandemic. According to the 24th March data, there is no cure for this viral acute respiratory disease, which caused 17,147 deaths. Healthcare professionals use medications used in previous coronavirus-induced diseases to relieve symptoms in treatment. Researchers, on the other hand, evaluate the comparative effects of these drugs and try to find a new drug or vaccine. We are publishing a study that biotechnological combinations of used and non-toxic effective drugs can be an effective approach to the disease.

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)0.003
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.026
Threshold uncertainty score0.087

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.003
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0260.005

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 head0.314
GPT teacher head0.464
Teacher spread0.150 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations2
Published2020
Admission routes1
Has abstractyes

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