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<i>In vitro</i>Evaluation of the Torsional Strength Reduction of Neonate Calf Metatarsal Bones with Bicortical Defects Resulting from the Removal of External Fixation Implants

2012· article· en· W1941955075 on OpenAlexaff
Stefano Brianza, Susan R. Vogel, Stephan Rothstock, André Desrochers, Ludovic Bouré

Bibliographic record

VenueVeterinary Surgery · 2012
Typearticle
Languageen
FieldMedicine
TopicBone fractures and treatments
Canadian institutionsUniversité de MontréalCegep de Saint Hyacinthe
Fundersnot available
KeywordsMedicineFixation (population genetics)Reduction (mathematics)Metatarsal bonesPopulationOrthodonticsAnatomy

Abstract

fetched live from OpenAlex

OBJECTIVE: To compare the torsional strength of calf metatarsal bones with defects produced by removal of 2 different implants. STUDY DESIGN: In vitro mechanical comparison of paired bones with bicortical defects resulting from the implantation of 2 different external fixation systems: the transfixation pin (TP) and the pin sleeve system (PS). SAMPLE POPULATION: Neonatal calf metatarsal bones (n = 6 pairs). METHODS: From each pair, 1 bone was surgically instrumented with 2 PS implants and the contralateral bone with 2 TP implants. Implants were removed immediately leaving bicortical defects at identical locations between paired metatarsi. Each bone was tested in torque until failure. The mechanical variables statistically compared were the torsional stiffness, the torque and angle at failure, and work to failure. RESULTS: For TP and PS constructs, respectively, there were no significant differences between construct types for any of the variables tested. Mean ± SD torsional stiffness: 5.50 ± 2.68 and 5.35 ± 1.79 (Nm/°), P = .75; torque: 57.42 ± 14.84 and 53.43 ± 10.16 (Nm); P = .34; angle at failure: 14.76 ± 4.33 and 15.45 ± 4.84 (°), P = .69; and work to failure 7.45 ± 3.19 and 8.89 ± 3.79 (J), P = .17). CONCLUSIONS: Bicortical defects resulting from the removal of PS and TP implants equally affect the investigated mechanical properties of neonate calf metatarsal bones.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.662
Threshold uncertainty score0.228

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.051
GPT teacher head0.300
Teacher spread0.250 · 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

Citations1
Published2012
Admission routes1
Has abstractyes

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