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Record W1543322321 · doi:10.1002/9781444345100.ch63

Distal Tibia/Plafond

2011· other· en· W1543322321 on OpenAlexaff
Hossein Pakzad, Peter J. O’Brien

Bibliographic record

VenueEvidence-Based Orthopedics · 2011
Typeother
Languageen
FieldMedicine
TopicBone fractures and treatments
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineSoft tissueExternal fixationReduction (mathematics)Internal fixationSurgeryDistal tibiaFixation (population genetics)OsteoarthritisTibiaExternal fixatorHigh energyRadiographySoft tissue injury

Abstract

fetched live from OpenAlex

Intra-articular fractures of the distal tibia secondary to high-energy trauma and axial loading are a challenge for orthopaedic surgeons. Careful assessment of the soft tissue injury and the fracture pattern are essential for planning surgical management. The historical literature indicates a high incidence of serious complications in patients treated with early open reduction and internal fixation (ORIF). Definitive management with external fixation and limited ORIF remains an appropriate treatment strategy in some situations. The most commonly applied treatment currently is a two-stage technique consisting of initial closed reduction and external fixation followed by definitive ORIF when the soft tissue envelope is less swollen. Infective complications may be reduced by this strategy. Posttraumatic osteoarthritis is a common finding on mid to long-term radiographic follow-up. Some degree of permanent disability is frequently associated with these complex injuries.

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)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.052
Threshold uncertainty score0.174

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0520.012

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 head0.053
GPT teacher head0.299
Teacher spread0.245 · 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
GenreOther

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
Published2011
Admission routes1
Has abstractyes

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