Bibliographic record
Abstract
Cox, Gerard 1 , Ryerson, Chris 2 and Wilcox, Pearce 2 . 1 McMaster University, Hamilton, 2 University of British Columbia, Vancouver. Introduction: There has been a remarkable increase in the number of well executed trials of management of Idiopathic Pulmonary Fibrosis (IPF) in the last 15 years. In addition, there have been major advances in the methods for diagnosis of this condition along with broader access to high resolution computed tomography (HRCT). However, diagnosis and management of IPF seem to remain quite varied even after publication of guidelines by international organizations. With the recent approval of an effective medical therapy it is plausible there will be substantial shift in practice – away from using unproven therapies in favour of an effective evidence-based strategy. Methods: Physicians across Canada were invited to complete a questionnaire survey. The electronic invitation was repeated after an interval of months to those who had not responded. Responses from 15 physisicians were collated anonymously. Results: The majority of responses came from physicians working in Ontario and British Columbia reflecting the high populations of these 2 provinces. Physicians from various practice settings, including solo, group, community-based and academic, were compared. Broad themes among the responses included reliance on non-invasive diagnostic testing, and low utilization of formal methods such as written protocols, composite assessment scales, and multidisciplinary conferencing. A wide range of therapies were prescribed. Monitoring for disease progression was most often done with tests of physiology and function. Acute exacerbations were reported in approximately 20% of patients. Conclusions: Current management of IPF by respiratory specialists in Canada reveals heterogeneity in prescribing practices, use of non-invasive diagnostic tests and preference for non-formal assessment methods. Supported by an educational grant from InterMune.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".