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Record W3162122341 · doi:10.1002/cpz1.135

SHIRPA as a Neurological Screening Battery in Mice

2021· article· en· W3162122341 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCurrent Protocols · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsForelimbReflexCerebellar DegenerationNeuroscienceCerebellumMotor coordinationPsychologyMedicinePhysical medicine and rehabilitation

Abstract

fetched live from OpenAlex

The SmithKline, Harwell, Imperial College, Royal Hospital, Phenotype Assessment (SHIRPA) is a rapid battery of tests comprising 42 measurements of motor activity, coordination, postural control, muscle tone, autonomic functions, and emotional reactivity, as well as reflexes dependent on visual, auditory, and tactile modalities. Individual scores in SHIRPA are sensitive in detecting phenotypes of several experimental models of neural disease, especially cerebellar degeneration and Alzheimer disease, and combined subscores have been useful in estimating the impact of vascular anomalies and exposure to infectious agents. In cerebellar degeneration, weak forelimb grip, impaired wire maneuver and air righting, and negative geotaxis appear as prevalent features. Most of the measures in the battery are susceptible to change after gene modifications or physiological alterations. SHIRPA can be used both in adult mice and mice in the preweaning period to screen for sensorimotor function and emotional reactivity, not selective attention or memory. © 2021 Wiley Periodicals LLC Basic Protocol: Step-by-step procedure for SHIRPA.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.874
Threshold uncertainty score0.450

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.052
GPT teacher head0.349
Teacher spread0.297 · 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