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Record W2611597785 · doi:10.1212/wnl.0000000000003892

Teaching Video Neuro <i>Images:</i> Lithium-induced reversible Pisa syndrome

2017· article· en· W2611597785 on OpenAlexafffund
Niraj Kumar, Dan A. Mendonça, Mandar Jog

Bibliographic record

VenueNeurology · 2017
Typearticle
Languageen
FieldMedicine
TopicParkinson's Disease and Spinal Disorders
Canadian institutionsWestern University
FundersAllerganAGE-WELLMerz PharmaceuticalsAcademic Medical Organization of Southwestern OntarioCanadian Institutes of Health ResearchLawson Health Research InstituteBoston Scientific Corporation
KeywordsLithium (medication)ParkinsonismNeurologyMedicineBipolar disorderAnesthesiaLithium carbonateInternal medicinePsychologyPsychiatryChemistry

Abstract

fetched live from OpenAlex

A 49-year-old man on chronic lithium therapy (1,500 mg/d) for bipolar disorder presented with a 2-year history of progressive left-lateral truncal flexion dystonia disappearing on lying supine (video 1 at [Neurology.org][1]), known as Pisa syndrome (PS), along with anterocollis and parkinsonism. Lithium serum level was normal (1.1 mmol/L). PS improved substantially 3 months after stopping lithium (video 2), supporting the diagnosis of lithium-induced PS (figure). PS has been reported with chronic use of a single or a combination of antipsychotics, but never with lithium monotherapy.1,2 Parkinsonism and PS may result from lithium-induced dopamine reuptake facilitation or dopamine receptor sensitivity reduction.2 [1]: http://neurology.org/lookup/doi/10.1212/WNL.0000000000003892

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)0.000
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.096
Threshold uncertainty score0.320

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0960.011

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 head0.024
GPT teacher head0.292
Teacher spread0.267 · 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

Citations7
Published2017
Admission routes2
Has abstractyes

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