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Record W1991107369 · doi:10.1503/cmaj.080757

Online medical blogging: don't do it!

2008· article· en· W1991107369 on OpenAlexaffvenue
Mark O. Baerlocher, Allan S. Detsky

Bibliographic record

VenueCanadian Medical Association Journal · 2008
Typearticle
Languageen
FieldHealth Professions
TopicHealth Literacy and Information Accessibility
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsViral loadMedicineFamily medicineHuman immunodeficiency virus (HIV)

Abstract

fetched live from OpenAlex

ABSTRACT To investigate the changes in Viral Load(VL) during Enhanced Adherence Counselling (EAC) sessions and its determinants among ART clients with unsuppressed VLs in Monze district. Method A Cross-sectional study involving 616 HVL ART clients from 15 health facilities in Monze district which was conducted between October 1 2019 and March 30 2021. Results Out of 616 clients analysed, there was an improvement in viral load suppression following completion of EAC with a final outcome of 61% suppression. 28.7% remained unsuppressed. A total of 9.1% had no final viral load results documented and 0.2 % had been transferred out of their respective facilities and were not included in the study. Collection of repeat Viral loads was done on 84% of the clients with high viral load results while 16% had no record of sample collection. A total of 56 results were not received giving a result return of 89% from repeat samples collected. Females had a 40% likelihood of being unsuppressed at 95% CI (41% to 86%) compared to the males. Conclusion EAC improves the outcomes of HVLs and should be encouraged on all high viral clients. Programs should be developed to improve suppression in females on ART

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)0.002
metaresearch head score (Gemma)0.010
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: Commentary · Consensus signal: none
Teacher disagreement score0.039
Threshold uncertainty score0.132

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0030.004
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0390.007

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 head0.042
GPT teacher head0.412
Teacher spread0.370 · 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
GenreCommentary

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

Citations7
Published2008
Admission routes2
Has abstractyes

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