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Record W2325871922 · doi:10.1097/bpb.0b013e32833ce484

Associated talocalcaneal and calcaneonavicular coalitions in the same foot

2010· article· en· W2325871922 on OpenAlexaff
Julio Javier Masquijo, James Jarvis

Bibliographic record

VenueJournal of Pediatric Orthopaedics B · 2010
Typearticle
Languageen
FieldMedicine
TopicFoot and Ankle Surgery
Canadian institutionsChildren's Hospital of Eastern OntarioUniversity of Ottawa
Fundersnot available
KeywordsMedicineAnkleFoot (prosody)Tarsus (eyelids)Tarsal BoneRadiographyComputed tomographySurgerySurgical planningRadiology

Abstract

fetched live from OpenAlex

UNLABELLED: Tarsal coalition represents abnormal fusion among two or more tarsal bones and is a frequent cause of foot and ankle pain. The coexistence of calcaneonavicular and talocalcaneal coalitions in the same foot has been rarely cited in the literature. We report three cases of rigid flatfoot associated to a double coalition in the same foot. Routine computed tomography (CT) scan helped to delineate the joint space narrowing and bony bridges for preoperative planning. All cases were treated surgically with lateral and medial approach, bar resection, and extensor digitorum brevis interposition. Resection of such coalitions produced variable clinical and radiographic results. The authors discuss the frequency of multiple tarsal bars and the importance of CT in preoperative planning. Multiple tarsal coalitions in the same foot are probably not rare. Surgical outcomes can be jeopardized if they are not recognized in advance. The detection, localization, and characterization of this entity with routine CT scan are mandatory in patients undergoing surgery. LEVEL OF EVIDENCE: IV.

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)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
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 head0.014
GPT teacher head0.267
Teacher spread0.252 · 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 designCase report
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

Citations25
Published2010
Admission routes1
Has abstractyes

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