Bibliographic record
Abstract
Since Charcot's description in 1869 and naming in 1874, ALS has been the coordinate degeneration of both corticospinal ('upper') motor neurons (CSMN; their axons in the lateral CST were observed as sclerotic, thus L[ateral] S[clerosis]) and spinal ('lower') motor neurons (SMN; 'anterior horn cells') that define ALS.Though not as absolutely purely motor system as long thought, before improved lifespan support enabled identification of cognitive/other involvement in ALS, these two neuron subtypes are still the defining and core, selectively vulnerable subtypes.Thus, it is critical to elucidate why these two quite distinct populations degenerate coordinately, in cortex and spinal cord, though developmentally born from distinct progenitor domains, with different neurotransmitter systems, synaptic types, and surrounding interneuron and astroglial types.Why do variants in genes expressed in every neuron type, including hundreds-thousands in cortex, cause disease risk, with (relatively) selective vulnerability?What is common with subtypes involved in FTD that might clarify shared vulnerabilities with ALS?Why do involved neurons function so well in people who later develop ALS (eg Lou Gehrig), indicating lack of early dysgenesis?Might complexity of evolutionary advancement in primate-human corticospinal system partially explain fragility/selective vulnerability of component neurons?Length and/or metabolic demands alone cannot-sensory DRG neurons and many cortical projection neurons are similarly long, yet not similarly involved.Bulbar ALS affects shorter neurons rather than longer CSMN.Some SMN subtypes survive.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.892 | 0.866 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".