Synuclein Meeting 2019: where we are and where we need to go
Bibliographic record
Abstract
The Synuclein Meetings are a series that has been taking place every 2 years for about 12 years. The Synuclein Meetings bring together leading experts in the field of synuclein and related human conditions with the goal of discussing and advancing the research. In 2019, the Synuclein Meeting is taking place in Ofir, a city in the outskirts of Porto, Portugal. The meeting is entitled 'Synuclein Meeting 2019: Where we are and where we need to go'. It has now been 22 years since the initial report of the genetic and pathological association between alpha-synuclein and Parkinson's disease (PD). The field has grown and matured, and major advances have been made. We are witnessing exciting times, with the first clinical trials being conducted that target synuclein, and bring the hope of novel therapies for patients with PD and their families. However, we still face many challenges and need to address fundamental questions for the field to progress to where we need to go: having biomarkers and effective therapies for PD and other synucleinopathies. In this context, we have designed the Synuclein Meeting 2019 with a different format. The program will include sessions in the format of a round-table discussion, to break away from the more rigid format of regular scientific meetings based on oral presentations. Our goal was to create opportunities for discussing the major questions in the field of synuclein and related human disorders, and challenge dogmatic ideas that require a critical revision in light of the most recent knowledge. In this issue, we assembled a series of comprehensive overviews of major topics, questions, and challenges in the field, that will be discussed in the meeting. We are confident that this special issue will be an instrumental reference for inspiring novel paths for future discoveries in the synuclein field and generate other discussions in the scientific community. This is the Preface for the Special Issue "Synuclein". Cover Image for this issue: doi: 10.1111/jnc.14520.
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 | 0.013 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.015 | 0.007 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.156 | 0.145 |
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".