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Record W2496263054 · doi:10.1385/0-89603-208-6:159

Primate Models of Parkinson's Disease

2003· book-chapter· en· W2496263054 on OpenAlexaff
Paul J. Bédard, R. Boucher, Baltazar Gomez‐Mancilla, Pierre Blanchette

Bibliographic record

VenueHumana Press eBooks · 2003
Typebook-chapter
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsMPTPDiseaseParkinson's diseaseNeurosciencePsychologyMedicinePathology

Abstract

fetched live from OpenAlex

An adequate animal model of a disease should reproduce the cardinal features of its human counterpart. Parkinson’s disease is characterized by akinesia, rigidity, and tremor. Attempts to reproduce Parkinsonian symptoms can be divided in three broad categories according to the method used. Earlier studies were based mostly on destruction of certain brain structures by surgical lesions with or without the help of stereotaxy. Then, with development of our knowledge of neurotransmitters, Parkinsonian features could be reproduced by drugs that affect more or less selectively certain biogenic amines. More recently, the serendipitous discovery of 1 methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) provided us with the best model of Parkinson’s disease to date. We will review these models,which have evolved over a period of over fifty years and have provided us with powerful tools to understand the pathophysiology of Parkinson’s disease and to test new therapeutic approaches.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.924
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.070
GPT teacher head0.280
Teacher spread0.211 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreOther

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

Citations8
Published2003
Admission routes1
Has abstractyes

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