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Record W2082783201 · doi:10.1136/ebn.6.4.124

Individuals taking combination therapies for HIV or AIDS faced barriers to remaining in, or returning to work

2003· letter· en· W2082783201 on OpenAlexaffabout
Irene Goldstone

Bibliographic record

VenueEvidence-Based Nursing · 2003
Typeletter
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsSt. Paul's Hospital
Fundersnot available
KeywordsHuman immunodeficiency virus (HIV)MedicineWeb of scienceFamily medicineInternal medicine

Abstract

fetched live from OpenAlex

Maticka-Tyndale E, Adam BD, Cohen JJ. To work or not to work: combination therapies and HIV. Qual Health Res2002 ; 12 : 1353 –72 [OpenUrl][1][CrossRef][2][PubMed][3][Web of Science][4] QUESTION: What are the labour force experiences of people living with HIV or AIDS who are taking combination therapies? Qualitative description. Windsor and Essex County region of Ontario, Canada. 35 people ≥18 years of age (89% men) who had tested positive for HIV, were taking combination therapies, and lived in or received AIDS services in Essex County were identified by the local HIV Care Program and AIDS Service Organization. Two thirds of participants were 30–39 years of age. Participants had been aware of their HIV positive status for <2 to >5 years. Individual, semistructured, indepth interviews were done between 1999 and 2000. Open ended questions addressed areas including treatment patterns, taking medications, symptom management strategies, work activities, relationships, life changes, and future plans. Interviews generally lasted 1–1.5 hours. Data analysis involved identifying clusters … [1]: {openurl}?query=rft.jtitle%253DQualitative%2BHealth%2BResearch%26rft.stitle%253DQual%2BHealth%2BRes%26rft.aulast%253DMaticka-Tyndale%26rft.auinit1%253DE.%26rft.volume%253D12%26rft.issue%253D10%26rft.spage%253D1353%26rft.epage%253D1372%26rft.atitle%253DTo%2BWork%2Bor%2BNot%2Bto%2BWork%253A%2BCombination%2BTherapies%2Band%2BHIV%26rft_id%253Dinfo%253Adoi%252F10.1177%252F1049732302238748%26rft_id%253Dinfo%253Apmid%252F12474908%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=10.1177/1049732302238748&link_type=DOI [3]: /lookup/external-ref?access_num=12474908&link_type=MED&atom=%2Febnurs%2F6%2F4%2F124.atom [4]: /lookup/external-ref?access_num=000179328400005&link_type=ISI

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.092
Threshold uncertainty score0.183

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.000

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 head0.098
GPT teacher head0.397
Teacher spread0.299 · 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 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

Citations1
Published2003
Admission routes2
Has abstractyes

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