MétaCan
Menu
Back to cohort
Record W3126027831 · doi:10.1016/j.ijid.2020.09.916

Identification of avian influenza viruses among birds in pet bird markets

2020· article· en· W3126027831 on OpenAlexaff
Mohammad Belayet Hossain, Najmul Haider, Katharine Sturm‐Ramirez, Rakib Al Hasan, Mohammad Enayet Hossain, M.Z. Rahman, Sukanta Chowdhury, Muzaffar G. Osmani, Shahzeb Khan, Eduardo Azziz‐Baumgartner, C. Todd Davis, N. S. Zeidner, Emma Kennedy

Bibliographic record

VenueInternational Journal of Infectious Diseases · 2020
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsInfluenza A virus subtype H5N1QuailBiologyPopulationCloacaAvian influenza virusVirologyVeterinary medicineVirusEcologyMedicineEnvironmental health

Abstract

fetched live from OpenAlex

Background: Avian influenza viruses (AIVs) are a significant public health and agricultural concern in Bangladesh. The human population typically lacks immunity to most of these viruses, posing a pandemic influenza threat. Since 2007, AIVs have been identified in live bird markets in Bangladesh. This study aimed to detect the AIV subtypes H5, H7, and H9 in pet bird markets (PBMs) in Bangladesh.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.039
GPT teacher head0.370
Teacher spread0.331 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Infectious DiseasesSame topicInfluenza Virus Research StudiesFrench-language works237,207