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Record W2039702214 · doi:10.1179/joc.2006.18.6.582

Gemifloxacin for the Management of Community-Acquired Respiratory Tract Infections

2006· review· en· W2039702214 on OpenAlexaff
J. Blondeau, Glenn Tillotson, Julie Deangelis

Bibliographic record

VenueJournal of Chemotherapy · 2006
Typereview
Languageen
FieldMedicine
TopicPneumonia and Respiratory Infections
Canadian institutionsRoyal University Hospital
Fundersnot available
KeywordsGemifloxacinStreptococcus pneumoniaeRespiratory tract infectionsMedicineAntibioticsAntimicrobialIntensive care medicineAntibacterial agentRespiratory tractAntibiotic resistanceMicrobiologyRespiratory systemBiologyInternal medicine

Abstract

fetched live from OpenAlex

Community-acquired lower respiratory tract infections (LRTIs) exert a growing clinical and financial burden on healthcare systems and employers. In addition, antimicrobial resistance among pathogens, such as Streptococcus pneumoniae, has compromised the use of commonly prescribed antimicrobial compounds. Newer fluoroquinolones have been developed to meet these emerging demands. Gemifloxacin is a potent, dual-acting fluoroquinolone with excellent activity against S. pneumoniae (MIC(90)0.03-0.06 microg/ml) including those strains demonstrating resistance to other classes of antibiotics. Gemifloxacin demonstrated excellent clinical success in community-acquired lower respiratory infections, has an acceptable safety profile, and is a cost-effective alternative in the management of LRTIs including those caused by resistant pathogens.

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)0.001
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.003

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 head0.085
GPT teacher head0.396
Teacher spread0.311 · 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

Citations5
Published2006
Admission routes1
Has abstractyes

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