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Record W4319989181 · doi:10.1039/d2md00149g

Design and synthesis of naturally-inspired SARS-CoV-2 inhibitors

2023· article· en· W4319989181 on OpenAlex
Haitham Hassan, Jeanne Chiavaralli, Afnan Hassan, Loay Bedda, Tim Krischuns, Kuang‐Yu Chen, Alice Shi Ming Li, Adrien Delpal, Étienne Decroly, Masoud Vedadi, Nadia Naffakh, Fabrice Agou, Sergio Mallart, Reem K. Arafa, Paola B. Arimondo

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

VenueRSC Medicinal Chemistry · 2023
Typearticle
Languageen
FieldComputer Science
TopicComputational Drug Discovery Methods
Canadian institutionsUniversity of Toronto
FundersNational Institute of Allergy and Infectious DiseasesFondation de FranceInstitut PasteurNational Institutes of HealthAgence Nationale de la Recherche
KeywordsCytotoxicityChemical spaceNatural productChemistryDocking (animal)ProteaseCombinatorial chemistryStereochemistryComputational biologyBiochemistryEnzymeIn vitroBiologyDrug discovery

Abstract

fetched live from OpenAlex

A naturally inspired chemical library of 25 molecules was synthesised guided by 3-D dimensionality and natural product likeness proved to have antiviral activity against SARS-CoV-2.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.120
Threshold uncertainty score0.517

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.033
GPT teacher head0.303
Teacher spread0.269 · 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