Protocol for the Stather Canadian Outcomes Registry for Chest ProcedurEs (SCOPE)
Bibliographic record
Abstract
INTRODUCTION: The Stather Canadian Outcomes registry for chest ProcedurEs (SCOPE registry) is a Canadian multicentre registry of chest procedures. METHODS AND ANALYSIS: The SCOPE registry is designed as a multicentre prospective database of specific bronchoscopic or other pulmonary procedures. Each procedure of interest will be associated with a registry module, and data capture designed to evaluate effectiveness of procedures on relevant patient outcomes. Participating physicians will be asked to enter data for all procedures performed in a given module. The anonymised dataset will be housed in a web-based electronic secure database. Specific modules included will be based on participating physician suggestions, capacity and consensus of the steering committee and relevance of hypotheses/research potential. ETHICS AND DISSEMINATION: The central registry is under approval from the Conjoint Health Research Ethics Board at the University of Calgary. We aim for registry data to lead to publication of manuscripts in international medical journals as the primary mode of dissemination. Data may also be used by local investigators for personal and/or institutional quality control purposes as well as to inform health policies. Data requests from non-participating investigators for use under ethics approved research protocols can be considered.
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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 | 0.064 | 0.103 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.229 | 0.048 |
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".