Bibliographic record
Abstract
Dr. James (Jim) Cameron Hogg’s pioneering research has profoundly shaped our understanding of Chronic Obstructive Pulmonary Disease (COPD) by uncovering the pivotal role of the small airways in airflow obstruction. In the 1960s, his innovative retrograde catheter studies demonstrated that airflow resistance in COPD is predominantly localized to airways less than 2 mm in diameter, shifting the focus of COPD research from large airways to small airway disease.Over the last 60 years, Dr. Hogg’s endless enthusiasm for research and innovative application of molecular and imaging technologies—from immunohistochemistry to RNA sequencing and micro-computed tomography (micro-CT) imaging—has uncovered key structural and functional changes in the small airways, including terminal bronchiole loss and its early role in chronic obstructive pulmonary disease (COPD) pathogenesis. These ground breaking insights continue to redefine COPD prevention, diagnosis and treatment.Dr. Hogg’s transformative mentorship has extended his impact beyond COPD, advancing research in asthma, cystic fibrosis and interstitial lung disease through his leadership of lung tissue biobanks and interdisciplinary collaborations. His enduring legacy, marked by genuine curiosity, innovation and collaboration, continues to inspire a new generation of researchers. By embracing emerging technologies Dr. Hogg has redefined COPD research, inspiring future generations to carry forward his vision and, in his words, “dream in technicolor.”
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".