MétaCan
Menu
Back to cohort

Prevention and treatment of respiratory viral infections: Presentations on antivirals, traditional therapies and host-directed interventions at the 5th ISIRV Antiviral Group conference

2017· article· en· W2770489650 on OpenAlexaff
Jennifer L. McKimm‐Breschkin, Shibo Jiang, David S.C. Hui, John H. Beigel, Elena A. Govorkova, Nelson Lee

Bibliographic record

VenueAntiviral Research · 2017
Typearticle
Languageen
FieldMedicine
TopicRespiratory viral infections research
Canadian institutionsUniversity of Alberta
FundersDivision of Cancer Epidemiology and Genetics, National Cancer InstituteNational Institute of Allergy and Infectious DiseasesNational Cancer InstituteU.S. Department of Health and Human ServicesNational Institutes of HealthNorth Carolina Department of Health and Human ServicesFoundation for the National Institutes of Health
KeywordsFavipiravirHuman metapneumovirusMedicineNitazoxanideVirologyClinical trialRespiratory tract infectionsImmunologyIntensive care medicineRespiratory systemInternal medicineCoronavirus disease 2019 (COVID-19)DiseaseInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.013
metaresearch head score (Gemma)0.007
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: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.070

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.007
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0050.004
Open science0.0020.005
Research integrity0.0100.012
Insufficient payload (model declined to judge)0.0140.003

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 head0.351
GPT teacher head0.496
Teacher spread0.145 · 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
GenreReview

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

Citations75
Published2017
Admission routes1
Has abstractno

Explore more

Same venueAntiviral ResearchSame topicRespiratory viral infections researchFrench-language works237,207