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Record W2495119955 · doi:10.1007/978-1-61779-301-1_21

Assessing Spinal Cord Injury

2011· book-chapter· en· W2495119955 on OpenAlexaff
Gillian D. Muir, Erin J. Prosser-Loose

Bibliographic record

VenueNeuromethods · 2011
Typebook-chapter
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsPhysical medicine and rehabilitationSpinal cord injuryForelimbComputer scienceReliability (semiconductor)RehabilitationMedicineSpinal cordPsychologyPhysical therapyNeuroscience

Abstract

fetched live from OpenAlex

Functional recovery is the ultimate goal of research into experimental therapy for spinal cord injury (SCI). The effective use of animal models of SCI requires functional assessment methods that can be reliably repeated in different laboratories. The aim of this chapter is to describe some key features of behavioural methodology which inform our laboratory’s decisions regarding appropriate assessments in rat models of SCI. These include recognition of the type of data being measured, assurance of appropriate sampling methods to improve reliability, and considerations of the animals’ motivation during completion of the behavioural tasks. We then illustrate these principles with methods used in our laboratory, a major emphasis of which has been biomechanical analysis of limb action during overground locomotion. We also describe analysis of skilled limb movements during more challenging tasks such as ladder locomotion and forelimb pellet retrieval. Our focus throughout is on objective quantitative assessment of movement that can be reliably used to assess functional capabilities in rat SCI models under different lesion or treatment conditions.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.965
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.312
GPT teacher head0.513
Teacher spread0.201 · 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; both teacher heads agree on what is shown here.

Study designOther design
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

Citations0
Published2011
Admission routes1
Has abstractyes

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