Bibliographic record
Abstract
James Cameron Hogg (Jim) was my principal career mentor and became a lifelong collaborator and friend. I met Jim at McGill shortly after he published his landmark paper in the New England Journal of Medicine (NEJM) identifying the small airways of the lung as the major site of increased airflow resistance in patients who had chronic obstructive pulmonary disease (COPD). As a teenager in Northern Ontario, Jim wanted to be a hockey player with the Flin Flon Bombers, a renowned team from Northern Manitoba but when his coach said he was unlikely to make the team he decided he better pursue a different career pathway; he chose Medicine and returned to Winnipeg and the University of Manitoba. He spent 3 years as a general medical officer in Greenwood Nova Scotia before doing his PhD and Pathology training at McGill and the Massachusetts General Hospital. In his PhD work Jim found that small airway resistance was less than 25% of total lower airway resistance in 16 normal human lungs but that these airways were the major site of airflow resistance in the lungs of 10 patients who had suffered with COPD. It is no exaggeration to say that this seminal observation represents the most important finding in the study of obstructive lung since Laennec’s description of the stethoscope. Following up on this observation became a major focus of Jim’s career. He has continued to ask questions about the small airways using progressively more sophisticated and accurate techniques to get answers.
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 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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.010 |
| Insufficient payload (model declined to judge) | 0.046 | 0.037 |
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".