Bibliographic record
Abstract
A classic and often quoted mode of progress in medical therapeutics is the connection from bench to bedside. In fact, many of our potent new therapeutic agents such as biologic drugs and Janus kinase inhibitors have been made possible because of biologic and mechanistic insights leading to these new treatments for complex autoimmune diseases. But what about research that evolves in the opposite direction? That is, first comes the observation of a particular clinical response phenomenon and then researchers circle back and try to determine what is driving the phenotypic patterns that are observed in the clinic. This is actually what has occurred with research into the possible mechanisms of action of methotrexate (MTX). This amazing drug has been in use for more than 60 years. It was a designer agent for the purpose of competing with intracellular reduced folates, ubiquitous cofactors for a host of critical enzymatic activities. The rationale was that if MTX could fool the cell into uptake, because of its resemblance to the necessary folate substrate, this Trojan horse could then interfere with normal function and serve as a useful tool for oncologists to use against various cancers. But before too long the drug was used for rapidly proliferating cutaneous cells (psoriasis) and then anecdotal, and later focused, studies to treat various forms of arthritis in the 1970s and 1980s. Clinicians were desperate for effective drugs that worked for challenging conditions such as psoriasis, as well as psoriatic and rheumatoid arthritis (RA). Thus, MTX had been used for years before its precise mechanism of action was understood, or how that … Address correspondence to Dr. J.M. Kremer, Center for Rheumatology, 1367 Washington Ave., Albany, New York 12206, USA. E-mail: jkremer{at}joint-docs.com
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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.015 |
| Insufficient payload (model declined to judge) | 0.014 | 0.009 |
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".