Bibliographic record
Abstract
The completion of the Human Genome Project, together with a better understanding of some of the emerging genetic patterns of human disease, has enabled a thorough examination of the most appropriate genetic models for amyotrophic lateral sclerosis (ALS). The pathology and epidemiology of ALS have been intensively studied since Adar, Charcot, and Duchenne first described the disease in the 1860s. Results of genetic studies that have emerged over the past two decades have led to the identification of SOD1 as a well-established causative gene for ALS. However, the identification of SOD1 has not been followed up by the identification of other genes responsible for classic ALS. This leads to the speculation that more complex genetic mechanisms are involved than initially assumed. While mutations in single genes are still likely to constitute a small proportion of ALS cases, the genes responsible for ALS in families with clusters of two or three affected individuals, and more particularly in sporadic cases, are far from being determined. Multigenic, somatic mutation, and gene–environment models may all contribute to the genetic etiology of ALS. The challenge now lies in determining which models are the most appropriate to dissect out the genetic components involved. This research will ultimately aid in identifying the cumulative risk of developing ALS. GLOSSARY: ALS = amyotrophic lateral sclerosis; FALS = familial ALS; FTD = frontotemporal dementia; HSP = hereditary spastic paraplegia; PDC = Parkinson-dementia complex; PLS = primary lateral sclerosis; PON = paraoxonase; SALS = sporadic ALS; SBMA = spinal and bulbar muscular atrophy; SMA = spinal muscular atrophy; SNP = single nucleotide polymorphism.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".