My Amyotrophic Lateral Sclerosis (ALS) Journey from Weakness to Diagnosis: A Journey of Hope
Bibliographic record
Abstract
Amyotrophic lateral sclerosis (ALS) or Lou Gehrig's disease is a progressive neurodegenerative disease that attacks and kills motor neurons in the brain and spinal cord, leading to muscle weakness and atrophy, eventually causing respiratory failure and death within 2-5 years after diagnosis. By 2040, the global population of individuals living with ALS is projected to approach 400,000. Since ALS was discovered by Charcot 150 years ago, only two drugs (Edaravone and Riluzole) have been available, offering modest clinical benefits in slowing disease progression. The increasing number of cases, along with the high costs of treatment and care, creates a growing burden on communities and the healthcare system. However, despite this rising burden and the failure of most clinical trials, the ALS community remains hopeful because of the patients themselves. ALS patients are the beating heart of the ALS community. They engage in efforts to improve lives for others, raising awareness through their real-life experiences, participating in research activities, fundraising, providing samples for research, and advocating strongly in front of communities and governments to raise funds. Their engagement is highly valuable, and collaboration with the research community is essential to understanding the disease process and developing effective disease-modifying therapies. Here, we share the story of Mrs. Sherry Wityshyn, an ALS patient and a true ALS warrior from Winnipeg, Manitoba, Canada. We believe her story will inspire and motivate the entire community to learn more about ALS. Furthermore, her story gives hope to everyone impacted. In this manuscript, we also emphasize the different stages of Sherry's journey from weakness to diagnosis and our efforts to share her enduring words with policymakers in the government.
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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 | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.018 |
| Scholarly communication | 0.013 | 0.014 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.008 | 0.032 |
| Insufficient payload (model declined to judge) | 0.007 | 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".