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Record W4389950499 · doi:10.1016/j.nmni.2023.101213

Raising awareness and mitigating risk of transmission of antimicrobial resistance during the upcoming 2024 Gangasagar religious mass gathering

2023· editorial· en· W4389950499 on OpenAlexaff
Avinash Sharma, Bhavuk Gupta, Abhrajyoti Ghosh, Shilpi Sharma, Alfonso J. Rodríguez‐Morales, Alimuddin Zumla, Ziad A. Memish

Bibliographic record

VenueNew Microbes and New Infections · 2023
Typeeditorial
Languageen
FieldImmunology and Microbiology
TopicAntibiotic Use and Resistance
Canadian institutionsInstitute of Infection and Immunity
FundersEuropean and Developing Countries Clinical Trials PartnershipHorizon 2020 Framework ProgrammeIndo-French Centre for the Promotion of Advanced ResearchDepartment of Biotechnology, Ministry of Science and Technology, IndiaNational Institute for Health and Care Research
KeywordsRaising (metalworking)Antibiotic resistanceTransmission (telecommunications)Resistance (ecology)Computer scienceMicrobiologyBiologyTelecommunicationsMaterials scienceEcologyAntibioticsMetallurgy

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 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)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.251
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.009
GPT teacher head0.242
Teacher spread0.233 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations2
Published2023
Admission routes1
Has abstractno

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