Bibliographic record
Abstract
Neuro Life Online® is an online platform delivering live-stream social and educational programs to the movement disorder community via Zoom video conferencing.\nIn 2016, PMDAlliance began testing Neuro Life Online® (NLO) as a pilot initiative to expand Parkinson’s disease education services in rural/underserved areas. NLO offers live-stream physician-based education, wellness coaching, social opportunities, and assistance in setting up telemedicine services for unserved and underserved populations across the US and internationally.\nThe need for more services is obvious. 19% of people in the US (60 million people) and 45% worldwide live in rural areas, based on a 2007 UN report. A 2015 study revealed severe depression and anxiety exists in 40-70% of people with PD and care partners - higher than most other chronic conditions. Only 20% receive treatment for their depression and anxiety, resulting in emergency room visits and increased mortality rates. A 2010 study linked overall physical and mental health to social relationships. Addressing health concerns without also addressing socialization and isolation issues results in poor outcomes. Conversely, when interventions are combined with community building and socialization, overall wellbeing is enhanced and follow through is improved.\nNLO was designed as a partnership program. Any clinician, allied health professional, or organization can engage as a partner and provide this program free of charge to their community, groups or patients and care system. Current users live across the US, in Canada, England, Australia, and Asia. Our growing network of 140 volunteer MDS physicians (called Physician Advisors) means that NLO live-streaming regularly offers the expertise of high-quality medical professionals to people living in areas not otherwise served. It offers socialization without regard to geographic location and focuses on the whole person’s health and wellbeing.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".