SHIRPA as a Neurological Screening Battery in Mice
Bibliographic record
Abstract
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.007 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.045 | 0.026 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".