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Record W2019893018 · doi:10.7547/0980014

Ability of Foot Care Professionals to Cast Feet Using the Nonweightbearing Plaster and the Gait-Referenced Foam Casting Techniques

2008· article· en· W2019893018 on OpenAlexaffabout
Leslie C. Trotter, M.R. Pierrynowski

Bibliographic record

VenueJournal of the American Podiatric Medical Association · 2008
Typearticle
Languageen
FieldMedicine
TopicFoot and Ankle Surgery
Canadian institutionsMcMaster UniversityCanadian Association of Occupational Therapists
Fundersnot available
KeywordsForefootMedicineFoot (prosody)Inter-rater reliabilityCastingReliability (semiconductor)Generalizability theoryFoot OrthosesOrthodonticsPhysical therapySurgeryComposite materialMathematicsMaterials scienceStatistics

Abstract

fetched live from OpenAlex

BACKGROUND: We examined the ability of foot care professionals to consistently capture the forefoot-to-rearfoot angular relationship of a single-cast foot. METHODS: Eleven Canadian certified pedorthists each cast a single foot twice using the plaster of Paris and foam box techniques. Three independent raters subsequently measured the resultant casts. Statistical analysis of the data provided generalizability coefficient estimates (rho(2)) of the intracaster, intercaster, and rater reliabilities. RESULTS: Intracaster reliabilities were excellent when the plaster and foam box techniques were used (rho(2) = 0.831 and 0.939, respectively). The casters were more intrareliable when foam was used (F = 2.755, P = .003). Intercaster reliabilities were poor for both techniques (rho(2) = 0.410 and 0.425). Although, intrarater reliability was excellent (rho(2) = 0.882), interrater reliability was poor (rho(2) = 0.418). CONCLUSION: Although plaster of Paris casting is widely perceived by the foot care community as the gold standard, other casting techniques may prove to be equally reliable.

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)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.101
Threshold uncertainty score0.632

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.020
GPT teacher head0.299
Teacher spread0.279 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations20
Published2008
Admission routes2
Has abstractyes

Explore more

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