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Record W2168076957 · doi:10.1177/1071100713508394

Gait Analysis in Orthopedic Foot and Ankle Surgery—Topical Review, Part 1

2013· review· en· W2168076957 on OpenAlexaff
D. Joshua Mayich, Alison C. Novak, Daniel Vena, Timothy R. Daniels, James W. Brodsky

Bibliographic record

VenueFoot & Ankle International · 2013
Typereview
Languageen
FieldMedicine
TopicDiabetic Foot Ulcer Assessment and Management
Canadian institutionsSt. Michael's HospitalToronto Rehabilitation InstituteSaint John Regional Hospital
Fundersnot available
KeywordsMedicineOrthopedic surgeryAnkleGaitPhysical medicine and rehabilitationFoot (prosody)Gait analysisFoot and ankle surgeryPhysical therapyExpert opinionSurgeryIntensive care medicine

Abstract

fetched live from OpenAlex

UNLABELLED: Gait analysis, the systematic study of human walking, is a field that has been studied for well over 100 years. With the technological and scientific advancements of the last several decades, there has been substantial improvement in our understanding of the mechanics of human walking. Particularly important has been the advancement in understanding of the differences between normal and pathological gait. The purpose of this paper is to review the principles of gait analysis, with a particular focus on the underlying methods and science. This will assist orthopedic foot and ankle surgeons in better understanding the methods and meaning of gait research and the publications that commonly appear in the orthopedic foot and ankle surgery literature. LEVEL OF EVIDENCE: Level V, expert opinion.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0060.007
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.055
GPT teacher head0.359
Teacher spread0.304 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations59
Published2013
Admission routes1
Has abstractyes

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