MétaCan
Menu
Back to cohort
Record W3032968571 · doi:10.14740/jnr.v0i0.582

A Case of Unsteady Gait: An Amyotrophic Lateral Sclerosis Mimic Causing Reversible Weakness

2020· article· en· W3032968571 on OpenAlexvenueno aff
Paola Martínez, Jonathan Donnelly, Humberto Leal-Bailey, Kyna Schreiber, Alicia S. Parker

Bibliographic record

VenueJournal of Neurology Research · 2020
Typearticle
Languageen
FieldMedicine
TopicAmyotrophic Lateral Sclerosis Research
Canadian institutionsnot available
Fundersnot available
KeywordsAmyotrophic lateral sclerosisMedicineWeaknessMotor neuronPhysical medicine and rehabilitationGaitHuman immunodeficiency virus (HIV)NeuroscienceDiseasePathologyAnatomyVirologyPsychology

Abstract

fetched live from OpenAlex

In this manuscript, we highlight the importance of human immunodeficiency virus (HIV) testing in patients presenting with a clinical picture suggestive of amyotrophic lateral sclerosis (ALS), particularly when there are other findings not consistent with a primary motor neuron disease. J Neurol Res. 2020;10(3):91-94 doi: https://doi.org/10.14740/jnr582

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.002
Science and technology studies0.0030.002
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0070.004
Insufficient payload (model declined to judge)0.0030.002

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.

Opus teacher head0.252
GPT teacher head0.399
Teacher spread0.147 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Neurology ResearchSame topicAmyotrophic Lateral Sclerosis ResearchFrench-language works237,207