1st International Congress on Clinical Neurology and Epidemiology
Bibliographic record
Abstract
About the CongressThe First International Congress on Clinical Neurology and Epidemiology (Neuroepidemiology) scheduled to take place in Munich, Germany in August 27-30, 2009 is a unique congress for many reasons.Neuroepidemiology has been perceived for a long time as a science of incidence, prevalence, risk factors, natural history and prognosis of neurological disorders.However, it is only one part of neuroepidemiology called nonexperimental neuroepidemiology.The other integral, but commonly forgotten, part of neuroepidemiology is an experimental neuroepidemiology, a research based on clinical trials of effectiveness or efficacy of various interventions in neurological disorders.This International Congress, for the first time, will bring together scientists and experts in all major fields of experimental and non-experimental neuroepidemiology.The Congress will feature internationally recognized invited speakers, platform lectures, oral presentations and poster sessions, and will provide an ideal platform for continuing education in all fields of experimental and nonexperimental clinical neuroepidemiology.
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 | 0.027 | 0.043 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.013 | 0.012 |
| Insufficient payload (model declined to judge) | 0.041 | 0.036 |
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".