Bibliographic record
Abstract
A 61-year-old man was being assessed for multiple sclerosis. His paired cerebrospinal fluid (CSF) and serum samples were sent to the clinical biochemistry laboratory for oligoclonal band analysis by CSF isoelectric focusing and IgG immunofixation (Fig. 1). Creutzfeldt–Jakob disease immunoassay panel with CSF 14-3-3, tau, and S100B proteins was negative. ... ... The answers are on the next page. Multiple IgG bands present in CSF but not in serum are diagnostic of oligoclonal bands, consistent with multiple sclerosis. Prominent serum bands triggered serum protein electrophoresis and immunofixation, which revealed coexisting IgG-kappa monoclonal protein (2.4 g/L). This pattern, multiple CSF bands with some accompanying serum bands, should be differentiated from the pattern of multiple similar CSF and serum bands present in systemic inflammation (1) and from monoclonal gammopathy, where 1 or 2 identical bands are found in CSF and serum (2). In addition, the serum bands in systemic inflammation tend to be small and evenly distributed (3).
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.006 |
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".