Bibliographic record
Abstract
The year 2015 marked the 20-year anniversary of the Pulmonary Pathology Society (PPS). It was founded in 1995, under the leadership of William Travis, MD (USA), with Thomas Colby, MD (USA); Samuel Hammar, MD (USA); Bruce Mackay, MD (USA); Helmut Popper, MD (Austria); and Osamu Matsubara, MD, PhD (Japan), among others. The PPS elected Dr Thomas Colby as its first president. Today, the PPS is an international society with 300 members from more than 25 countries. The PPS is a partner society with the College of American Pathologists (CAP) and the 2 organizations have cosponsored a number of educational activities and courses together at the CAP annual meeting and elsewhere for the past decade. The PPS has held an annual companion meeting at the United States and Canadian Academy of Pathology meeting each year since 1996 and a stand-alone meeting every 2 years.The 2015 PPS Biennial Meeting was cosponsored by the CAP and was held in San Francisco in June. Hosted by now past-president Kevin O. Leslie, MD, the 3-day meeting was likened by one colleague as “science fiction coming true.” The lecture lineup, carefully selected by an all-star Program Committee chaired by Philip T. Cagle, MD, a former president of the PPS, provided hot-off-the-press insight into one pulmonary pathology topic after another. It is from those presentations that most of the articles included in Part I of this Archives Special Section arise.As president of the PPS, it is a privilege and a pleasure to present this Special Section. Erik Thunnissen, MD, PhD, and colleagues provide a sophisticated discussion of how we can reduce medical error by identifying ex vivo artifacts in lung specimens; Maxwell Smith, MD, updates our understanding of interstitial lung disease; and Anja Roden, MD, and Eunhee Yi, MD, expand our understanding of pulmonary Langerhans cell histiocytosis. Further, Aliya Husain, MD, and Edward Garrity, MD, discuss airway changes in patients with lung transplants; Eric Bernicker, MD, describes how a team of clinicians, basic scientists, and pathologists can work together to make true personalized lung cancer therapy a reality; and Keith Kerr, BSc, MB, ChB, FRCPath, FRCPE, and Marianne Nicolson, MD, FRCP, provide a fascinating examination of PD-L1 as the “third dimension” of lung cancer therapy. We had a number of abstracts presented at the meeting that are included in this Special Section as well. Part II will continue the discussion of lung pathology from other PPS members.Many thanks to these pulmonary pathologists for sharpening the cutting edge of pulmonary pathology diagnosis and therapy.
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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.077 | 0.054 |
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".