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Ultrasonic and radiographic study of laxity in hip joints of young dogs

2007· article· en· W1969883253 on OpenAlexaboutno aff
B.D. Rocha, R.C.S. Tôrres

Bibliographic record

VenueArquivo Brasileiro de Medicina Veterinária e Zootecnia · 2007
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Orthopedics and Neurology
Canadian institutionsnot available
Fundersnot available
KeywordsRadiographyMedicineNuclear medicineDistractionAcetabulumOrthodonticsPositive correlationDentistryRadiologySurgeryInternal medicinePsychology

Abstract

fetched live from OpenAlex

In the present study, 22 hip joints of Whippet (four), Rottweiler (five) and Labrador Retriever (two) young dogs were evaluated with the aim of comparing the ultrasonic examination of coxofemoral joints with the radiographic evaluations, both distraction and conventional procedures, for the early diagnosis of passive laxity. The study was based on static ultrasonography, conventional radiography (CR) and distraction radiography (DR) methods. In order to quantify the relationship between the femur head and the acetabulum, the alpha (alpha) and gamma (gamma) angles were measured by ultrasonographic examination, the Norberg angle (NA) was measured by CR, and the distraction index (DI) was measured by DR. It was observed a negative correlation between angles alpha and gamma (r= -0,756; P<0.001) and correlation between DI and NA (r= -0.474; P<0.026). No correlation was observed between angles alpha and gamma in relation to DI and NA (alpha and DI: r= -0.380; P<0.081; alpha and NA: r= 0.013; P<0.954; gamma and DI: r= 0.338; P<0.124; gamma and NA: r= -0.192; P<0.391). The static ultrasonographic did not prove to be a sensitive method to earlier detection of passive laxity of coxofemoral joints in dogs aging 14 and 15 day-old. The distraction index of DR was efficient in early detecting the passive laxity in dogs averaging five months old, when compared to the NA of CR. Two false negative dogs were detected by the DI. The CR method was relevant to detect osteoarthritis alterations, helping the diagnosis of hip dysplasia (HD).

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.167
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.049
GPT teacher head0.327
Teacher spread0.278 · 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.

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

Citations12
Published2007
Admission routes1
Has abstractyes

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