Introduction - 2nd Dubrovnik International Conference on Multiple Sclerosis
Bibliographic record
Abstract
The past several years have seen a change of emphasis in the meetings devoted to multiple sclerosis (MS) due to the exciting new developments in the long-term treatment of the disease, giving hope to patients, and new therapeutic tools to their neurologists. Nevertheless, many questions remain regarding the exact pathogenesis and etiological factors of the disease. The matter of MS as a single disease, possibly with different pathogenetic mechanisms and/or different phenotypic expressions, or separate disease entities with diverse genetic characteristics, is still unsettled, as is the nosological situation of the eponymic variants of MS, Marburg’ s, Schilder’ s, Balo’ s and Devic’ s diseases. It is abundantly clear that all recurrent demyelinating conditions are not always MS, so that alternative diagnoses must be considered before initiating immunomodulatory or other forms of long-term treatment. Other important questions that remain unanswered are: will it ever be possible to identify families at risk for the disease by means of MRI and/or sophisticated genetic testing? Is there evidence that a pre-disease condition, the “ MS trait” exists and would its identification be the long-sought means for preventing the development of the disease? Discussions of immunomodulatory and other forms of long term treatment are not only understandable, but also most desirable, since a consensus has not yet been reached regarding many of its aspects, such as choice of specific agents, single versus multiple drugs, and optimum dosage and route of administration. An objective critique of the methodology of therapeutic trials should help treating neurologists better appreciate the impact of the available drugs and those still under investigation. The cost of many of these medications remains very high, adding to the already heavy financial burden of the disease itself on health care systems. Not every neurologist believes that all patients with MS should receive one of the available treatments, and a more thorough understanding of the natural history of the disease may prove critical in choosing the right patient for the right drug, or none at all. Some of these issues were addressed during the First International Dubrovnik Conference on MS in May 2001, and will again be examined with the added experience of two more years. We believe that these unresolved questions were sufficient reasons for convening this Second International Dubrovnik Conference on Multiple Sclerosis and inviting distinguished experts from Canada, Croatia, France, Germany, Israel, Poland, Spain, Switzerland, the United Kingdom and the USA to give us the benefit of their knowledge and wisdom.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.039 | 0.021 |
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".