The justification for the progressive fibrotic phenotype
Bibliographic record
Abstract
PURPOSE OF REVIEW: Describe the concept and recent data for the concept of progressive fibrotic interstitial lung disease (ILD). RECENT FINDINGS: Making an accurate diagnosis is critical to help determine appropriate therapy and predict prognosis. This is certainly true in the field of ILD where a diagnosis of idiopathic pulmonary fibrosis (IPF) leads a clinician to consider initiation of antifibrotic therapy, and avoidance of immunosuppression due to possible harm, at the time of diagnosis due to the high probability of disease progression. In other types of ILD immunosuppression may be helpful such as those associated with a connective tissue disease or in combination with antigen avoidance in hypersensitivity pneumonia. It is also recognized that despite initial approaches to therapy some non-IPF ILDs will develop progressive fibrosis leading to increased symptoms, decreased quality of life and early mortality. Once fibrosis is present, the biologic pathways responsible for progression can be redundant and respond in a similar fashion to antifibrotic therapy independent of the underlying disease. SUMMARY: There are clinical and biological rationale for the justification of a progressive fibrotic phenotype that complements the therapeutic decisions and prognosis provided by initial diagnosis.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".