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Record W2971913478 · doi:10.3348/kjr.2019.0181

Imaging of Thoracic Wall Abnormalities

2019· article· en· W2971913478 on OpenAlexaff
Alexandre Semionov, John Kosiuk, Amr M. Ajlan, Federico Discepola

Bibliographic record

VenueKorean Journal of Radiology · 2019
Typearticle
Languageen
FieldMedicine
TopicCongenital Diaphragmatic Hernia Studies
Canadian institutionsMcGill University Health CentreJewish General HospitalMontreal General Hospital
Fundersnot available
KeywordsMedicineThoracic wallRadiology

Abstract

fetched live from OpenAlex

Identification of certain abnormalities of the chest wall can be extremely helpful in correctly diagnosing a number of syndromic conditions and systemic diseases. Additionally, chest wall abnormalities may sometimes constitute diagnoses by themselves. In the present pictorial essay, we review a number of such conditions and provide illustrative cases that were retrospectively identified from our clinical imaging database. These include pentalogy of Cantrell, Klippel-Feil syndrome, cleidocranial dysplasia, Poland syndrome, osteopetrosis, neurofibromatosis type 1, Marfan syndrome, Gardner syndrome, systemic sclerosis, relapsing polychondritis, polymyositis/dermatomyositis, ankylosing spondylitis, hyperparathyroidism, rickets, sickle cell anemia, thalassemia, tuberculosis, septic arthritis of the sternoclavicular joint, elastofibroma dorsi, and sternal dehiscence.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.337

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.013
GPT teacher head0.286
Teacher spread0.274 · 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

Citations19
Published2019
Admission routes1
Has abstractyes

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