MétaCan
Menu
Back to cohort
Record W2121622907 · doi:10.3389/fneur.2015.00076

Future Scenarios for Levodopa-Induced Dyskinesias in Parkinson’s Disease

2015· article· en· W2121622907 on OpenAlexaff
Antonio Cerasa, Giacomo Koch, Alfonso Fasano, Francesca Morgante

Bibliographic record

VenueFrontiers in Neurology · 2015
Typearticle
Languageen
FieldMedicine
TopicNeurological disorders and treatments
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLevodopaMovement disordersParkinson's diseasePhysical medicine and rehabilitationNeuroscienceDiseaseMedicinePsychologyInternal medicine

Abstract

fetched live from OpenAlex

fter its first use in clinic since 1960, oral administration of l-3,4-dihydroxyphenylalanine (levodopa) remains the main treatment for Parkinson’s disease (PD) patients. Although the vast majority respond positively to treatment, a significant proportion of PD patients develop daily fluctuations in mobility and troublesome involuntary movements known as levodopa-induced dyskinesias (LIDs). The time-to-onset and severity of this motor complication show large individual variability thus limiting the long-term use of levodopa and clinical strategies aimed at reducing LIDs manifestation. In the last few years, a considerable effort has been made to understand the neurobiological basis of this motor complication. In particular, recent evidence coming from human and animal studies has strongly contributed to reduce the gaps in our knowledge of LIDs pathogenesis.

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)0.004
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.020
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.003
Scholarly communication0.0020.005
Open science0.0020.002
Research integrity0.0090.005
Insufficient payload (model declined to judge)0.0200.006

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.

Opus teacher head0.032
GPT teacher head0.277
Teacher spread0.244 · 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 designTheoretical or conceptual
Domainnot available
GenreReview

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

Citations5
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueFrontiers in NeurologySame topicNeurological disorders and treatmentsFrench-language works237,207