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Record W2974645752 · doi:10.1128/aac.00871-19

Prophylaxis of Mycobacterium tuberculosis H37Rv Infection in a Preclinical Mouse Model via Inhalation of Nebulized Bacteriophage D29

2019· article· en· W2974645752 on OpenAlexaff
Nicholas B. Carrigy, Sasha E. Larsen, Valerie A. Reese, Tiffany Pecor, Melissa Harrison, Philip J. Kuehl, Graham F. Hatfull, Dominic Sauvageau, Susan L. Baldwin, Warren H. Finlay, Rhea N. Coler, Reinhard Vehring

Bibliographic record

VenueAntimicrobial Agents and Chemotherapy · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsUniversity of Alberta
FundersNational Institute of Allergy and Infectious DiseasesNational Institutes of Health
KeywordsAerosolizationMycobacterium tuberculosisInhalationTuberculosisMedicineBacteriophageNebulizerImmunologyVirologyMicrobiologyAnesthesiaPathologyChemistryBiologyEscherichia coli

Abstract

fetched live from OpenAlex

Globally, more people die annually from tuberculosis than from any other single infectious agent. Unfortunately, there is no commercially available vaccine that is sufficiently effective at preventing the acquisition of pulmonary tuberculosis in adults. In this study, preexposure prophylactic pulmonary delivery of active aerosolized antituberculosis bacteriophage D29 was evaluated as an option for protection against Mycobacterium tuberculosis infection.

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 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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.572
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.257
Teacher spread0.246 · 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 designBench or experimental
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

Citations60
Published2019
Admission routes1
Has abstractyes

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