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Record W2969116354 · doi:10.1152/jn.00233.2019

Animal models of developmental motor disorders: parallels to human motor dysfunction in cerebral palsy

2019· article· en· W2969116354 on OpenAlexaff
Clarissa F. Cavarsan, Monica A. Gorassini, Katharina A. Quinlan

Bibliographic record

VenueJournal of Neurophysiology · 2019
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsUniversity of Alberta
FundersNational Institute of Neurological Disorders and Stroke
KeywordsNeuroscienceCerebral palsySpasticityPsychologyPhysical medicine and rehabilitationMotor systemAnimal modelMedicineInternal medicine

Abstract

fetched live from OpenAlex

Cerebral palsy (CP) is the most common motor disability in children. Much of the previous research on CP has focused on reducing the severity of brain injuries, whereas very few researchers have investigated the cause and amelioration of motor symptoms. This research focus has had an impact on the choice of animal models. Many of the commonly used animal models do not display a prominent CP-like motor phenotype. In general, rodent models show anatomically severe injuries in the central nervous system (CNS) in response to insults associated with CP, including hypoxia, ischemia, and neuroinflammation. Unfortunately, most rodent models do not display a prominent motor phenotype that includes the hallmarks of spasticity (muscle stiffness and hyperreflexia) and weakness. To study motor dysfunction related to developmental injuries, a larger animal model is needed, such as rabbit, pig, or nonhuman primate. In this work, we describe and compare various animal models of CP and their potential for translation to the human condition.

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)0.002
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.022
GPT teacher head0.263
Teacher spread0.242 · 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 designBench or experimental
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

Citations44
Published2019
Admission routes1
Has abstractyes

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