Bibliographic record
Abstract
Cellular communication network factor 2 (CCN2, formerly known as ‘connective tissue growth factor’ or ‘CTGF’) was the subject of anti-fibrotic drug development programs, largely in FibroGen, starting in the mid-1990s. This led to the development of FG-3019 (pamrevlumab) as a lead drug that was used initially to target diabetic nephropathy and subsequently pancreatic cancer, pulmonary fibrosis and Duchenne’s muscular dystrophy. All these programs failed clinically; diabetes in early development, and the others at Phase III. Could these failures have been anticipated? Is ‘CTGF’ dead as an anti-fibrotic target? What might have been done differently or could be done differently in the future? This personal commentary—based on years of experience first at FibroGen working on the ‘CTGF’ program and then as an independent academic researcher---aims to address at least some of these issues.
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 | 0.006 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.014 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.024 | 0.033 |
| Insufficient payload (model declined to judge) | 0.003 | 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".