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Record W4309933711 · doi:10.3389/fgene.2022.996364

Clinical genetics of spondylocostal dysostosis: A mini review

2022· review· en· W4309933711 on OpenAlexaff
Muhammad Umair, Muhammad Younus, Sarfraz Shafiq, Anam Nayab, Majid Alfadhel

Bibliographic record

VenueFrontiers in Genetics · 2022
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCraniofacial Disorders and Treatments
Canadian institutionsWestern University
FundersKing Abdullah International Medical Research Center
KeywordsBiologyMolecular geneticsCandidate geneIdentification (biology)Computational biologyGeneticsBioinformaticsGeneDiseaseMedicinePathology

Abstract

fetched live from OpenAlex

Spondylocostal dysostosis is a genetic defect associated with severe rib and vertebrae malformations. In recent years, extensive clinical and molecular diagnosis advancements enabled us to identify disease-causing variants in different genes for such severe conditions. The identification of novel candidate genes enabled us to understand the developmental biology and molecular and cellular mechanisms involved in the etiology of these rare diseases. Here, we discuss the clinical and molecular targets associated with spondylocostal dysostosis, including clinical evaluation, genes, and pathways involved. This review might help us understand the basics of such a severe disorder, which might help in proper clinical characterization and help in future therapeutic strategies.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.965
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.043
GPT teacher head0.367
Teacher spread0.324 · 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 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

Citations18
Published2022
Admission routes1
Has abstractyes

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