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Record W2245076737 · doi:10.1155/2013/248167

Quantitative Sputum Cell Counts to Monitor Bronchitis: A Qualitative Study of Physician and Patient Perspectives

2013· article· en· W2245076737 on OpenAlexaff
Liesel D’silva, Helen Neighbour, Amiram Gafni, Katherine Radford, Frederick E. Hargreave, Parameswaran Nair

Bibliographic record

VenueCanadian Respiratory Journal · 2013
Typearticle
Languageen
FieldMedicine
TopicAsthma and respiratory diseases
Canadian institutionsMcMaster UniversitySt. Joseph’s Healthcare Hamilton
Fundersnot available
KeywordsMedicineSputumBronchitisChronic bronchitisInternal medicineAsthmaIntensive care medicineAirwayImmunologyPathologyTuberculosisSurgery

Abstract

fetched live from OpenAlex

Many common diseases affecting the airways are characterized by airway inflammation. The measurement of this inflammation has a significant role in the management of these diseases. Quantitative sputum cell counts provide a measurement of the type and severity of inflammation present. Sputum cell counts are used in routine clinical practice in some centres but their use is not widespread. The present study used a standardized questionnaire to determine both patients' and physicians' attitudes toward the use of sputum cell counts. The use of sputum cell counts was well accepted by patients and physicians. Ninety per cent of patients were satisfied with the test. Sixty per cent of family physicians were satisfied with the test and 80% were in favour of it being funded by the government. The authors recommend more widespread use of sputum cell counts to guide the management of airway diseases.

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)0.023
metaresearch head score (Gemma)0.041
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.123

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.041
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0030.004
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.308
Teacher spread0.288 · 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 designQualitative
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

Citations8
Published2013
Admission routes1
Has abstractyes

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