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Record W2119588720 · doi:10.2522/ptj.20090399

Proprioceptive Acuity Assessment Via Joint Position Matching: From Basic Science to General Practice

2010· article· en· W2119588720 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePhysical Therapy · 2010
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsCanadian Institutes of Health Research
FundersCanadian Institutes of Health Research
KeywordsProprioceptionMatching (statistics)Perspective (graphical)PsychologyPhysical medicine and rehabilitationPosition (finance)Test (biology)Position paperCognitive psychologyComputer scienceMedicineArtificial intelligence

Abstract

fetched live from OpenAlex

Over the past several decades, studies of use-dependent plasticity have demonstrated a critical role for proprioceptive feedback in the reorganization, and subsequent recovery, of neuromotor systems. As such, an increasing emphasis has been placed on tests of proprioceptive acuity in both the clinic and the laboratory. One test that has garnered particular interest is joint position matching, whereby individuals must replicate a reference joint angle in the absence of vision (ie, using proprioceptive information). On the surface, this test might seem straightforward in nature. However, the present perspective article informs therapists and researchers alike of multiple insights gained from a recent series of position matching studies by the author and colleagues. In particular, 5 factors are outlined that can assist clinicians in developing well-informed opinions regarding the outcomes of tests of position matching abilities. This information should allow for enhanced diagnosis of proprioceptive deficits within clinical settings in the future.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.462

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 communication0.0000.001
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 head0.037
GPT teacher head0.340
Teacher spread0.302 · 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