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Record W7036106910

Antibiotic prescription patterns amongst children residing in remote Northern Manitoba communities

2015· other· en· W7036106910 on OpenAlexfundaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2015
Typeother
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPhytochemical Studies and Bioactivities
Canadian institutionsnot available
FundersResearch ManitobaHealth Sciences Centre Research FoundationHeart and Stroke Foundation of Canada
KeywordsNucleofectionFusible alloyHyporeflexiaCircumstantial evidenceTSG101Diafiltration
DOInot available

Abstract

fetched live from OpenAlex

In recent years, there has been growing concerns with respect to health care providers in relation to over-prescription of antibiotics in a primary care setting, compounding the rising concerns of antibiotic resistance. There currently is a deficit in the literature with respect to prescription patterns being quantified and reported as it pertains to children and adolescents residing in remote northern Manitoba communities. We sought to address this discrepancy in the literature via evaluating trending data regarding antibiotic prescription patterns in select remote northern communities in Manitoba in children aged 0 to 19. We attempted to address this discrepancy in the literature via evaluating trending data regarding antibiotic prescription patterns in select remote northern communities in Manitoba in children aged 0 to 19. Our results show preliminary evidence of decreasing rates of antibiotic prescriptions in remote northern Manitoba communities. More work is necessary to get a broader picture of past and current antibiotic prescription patterns in order to serve as a catalyst for clinical guideline reforms when necessary, to give us a better picture of the overall quality of care these patients receive and ultimately to improve the health outcomes of patients in these communities

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.859
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)0.0000.000

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 head0.014
GPT teacher head0.195
Teacher spread0.182 · 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 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

Citations0
Published2015
Admission routes2
Has abstractyes

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