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Record W4309559238 · doi:10.1097/mop.0000000000001204

Update of surgical treatment of polydactyly

2022· review· en· W4309559238 on OpenAlexaff
Yaser Tawfeeq, J. Michael Hendry, Kristi Sue Wood

Bibliographic record

VenueCurrent Opinion in Pediatrics · 2022
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCongenital limb and hand anomalies
Canadian institutionsKingston Health Sciences CentreQueen's University
Fundersnot available
KeywordsMedicinePolydactylyPhalanxDeformitySoft tissueSurgerySyndactylyAnatomy

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: Polydactyly presents with variable extent of duplication and may involve preaxial/radial (hand)/medial (foot), postaxial/ulnar (hand)/lateral (foot) or central duplication. This review will summarize recent advancements in the surgical management of this common entity. RECENT FINDINGS: Modifications to classification systems aim to help guide surgical management of polydactyly. Attempts have been made at quantifying preoperative angulation of the duplicated digits to minimize the chance of residual or recurrent deformity after surgical reconstruction. As a result, consideration should be given to the need for soft tissue correction vs. osteotomy to optimize the clinical outcome. On-top plasty is an option that may be beneficial in 'unequal' preaxial polydactyly, where neither duplicate is preferred on its own. SUMMARY: Polydactyly is one of the most common congenital anomalies in the hands and feet. Determination of surgical intervention often begins with classification systems that exist, which primarily separate these into preaxial, postaxial, and central. Referral for surgical consideration is indicated, given the management is often surgical.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.998
Threshold uncertainty score0.789

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.080
GPT teacher head0.377
Teacher spread0.297 · 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 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

Citations5
Published2022
Admission routes1
Has abstractyes

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