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Record W2046946822 · doi:10.4103/0970-0218.58403

Nasal carriage of methicillin resistant Staphylococci in healthy population of East Sikkim

2009· article· en· W2046946822 on OpenAlexaboutno aff
Ankur Barua, Devjyoti Majumdar, Barnali Paul

Bibliographic record

VenueIndian Journal of Community Medicine · 2009
Typearticle
Languageen
FieldMedicine
TopicAntimicrobial Resistance in Staphylococcus
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCarriageMethicillin-resistant Staphylococcus aureusStaphylococcus aureusEpidemiologyPopulationEnvironmental healthInternal medicineBiologyBacteriaPathology

Abstract

fetched live from OpenAlex

Methicillin resistant Staphylococcus aureus (MRSA) strains were initially described in 1961 and emerged in the last decade as one of the most important nosocomial pathogens. MRSA is a strain of S. aureus that has developed resistance to methicillin and other beta β- lactamase-resistant penicillins and cephalosporins.(1) MRSA infections have recently been identified in the community, which raised a question of whether these infections were transmitted from hospital, or they were caused by different resistant strains. The sharp increase in the prevalence of MRSA acquired infections in many communities had led to the consideration of outpatients as a source of infection in an institution.(2) Epidemiology of MRSA in the community is little understood or not studied at length. A few reports on MRSA in the healthy population of Nigeria, USA, Canada, Pakistan and Japan are available in the world literature. Till the beginning of study no report on the prevalence of MRSA in the community in India was available. Case reports of community acquired MRSA infections had been increasing since last 3 years in the tertiary care level hospitals in Gangtok of East Sikkim. Hence, a study was undertaken to determine the prevalence of MRSA among healthy subjects in the community in Gangtok of East Sikkim in India.

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.749
Threshold uncertainty score0.838

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.044
GPT teacher head0.346
Teacher spread0.301 · 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.

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

Citations14
Published2009
Admission routes1
Has abstractyes

Explore more

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