Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Biologics have revolutionized several areas of medical therapeutics, and dozens of them are used by millions of patients. Monoclonal antibodies are only one type of biologics, but more than 900 are now in different phases of development. These drugs are complex to make and not cheap. The market is constantly increasing, and several biosimilars (copies of biologics) are being used, while many are still waiting to become available to the public. Biosimilars are more complex than generics, and regulatory agencies have very stringent criteria for approval. In the IBD field, the biosimilar infliximab (Inflectra®, Remsima®) has been recently approved by the EMA, but not by Canadian authorities. The EMA has considered that 'high similarity' in preclinical studies together with clinical data from two trials in ankylosing spondylitis and rheumatoid arthritis warrant the 'extrapolation' for all approved indications for original infliximab (Remicade®), specifically Crohn's disease and ulcerative colitis. Canadian authorities have not accepted extrapolation, based on differences in glycosylation (fucosylation) that could be related to properties important in Crohn's disease. Most scientific societies do support the idea of asking for specific clinical trials before approval, although they acknowledge that following EMA, FDA, and WHO guidelines warrant safe products. Practical issues such as interchangeability and substitution remain unsolved, and it is very likely that there will be different solutions at the national level. Pharmacovigilance plans will be key for obtaining reliable data. Biosimilars are not better drugs, but can be clearly cheaper and may facilitate access to new treatments in many populations.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 it