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Record W4405644535 · doi:10.2519/josptcases.2024.0086

The Clinical Diagnosis and Treatment of an Anterior Calcaneal Process Fracture Overlooked on Imaging: A Case Study

2024· article· en· W4405644535 on OpenAlexaboutno aff
Teri Gilbert-Hogan

Bibliographic record

VenueJOSPT Cases · 2024
Typearticle
Languageen
FieldMedicine
TopicFoot and Ankle Surgery
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineFracture (geology)Calcaneal fractureOrthodonticsRadiologyCalcaneusSurgeryGeology

Abstract

fetched live from OpenAlex

BACKGROUND: Anterior calcaneal process fractures are often overlooked on radiographs. Given a similar clinical presentation, these fractures are frequently misdiagnosed as lateral ankle sprains. CASE DESCRIPTION: A 43-year-old male was referred to physical therapy following an inversion ankle injury. Sites of interest identified on initial radiography were asymptomatic, including an os trigonum and possible dorsal talar avulsion fracture. Screening with the Ottawa ankle rules was negative. His clinical presentation was similar to an inversion ankle sprain with concordant swelling and pain. OUTCOME: Subsequent ankle imaging was completed following a lack of expected clinical progression, revealing a subtle calcaneal fracture overlooked on initial imaging. The patient was referred to orthopedics and managed in a boot with partial weight-bearing. He was released to full weight-bearing 6 weeks later with resolution of pain and gradual recovery of normalized range of motion and strength. DISCUSSION: Improving proficiency of interpreting radiograph images as physical therapists, application of the four-eyes principle when reading images, and awareness of potential fractures with negative Ottawa ankle rules screening are beneficial to early and accurate diagnosis and treatment of foot fractures. JOSPT Cases 2025;5(1):12-17. Epub 20 December 2024. doi:10.2519/josptcases.2024.0086

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.321
Threshold uncertainty score0.291

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 communication0.0000.000
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 head0.061
GPT teacher head0.418
Teacher spread0.357 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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