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Record W2027093723 · doi:10.14740/jcgo.v4i1.306

Maternal Genetic Skeletal Disorders: Lessons Learned From Cases of Maternal Osteogenesis Imperfecta and Fibrodysplasia Ossificans Progressiva

2015· article· en· W2027093723 on OpenAlexvenueno aff
Rachel Shulman, Jane Ellis, Eileen M. Shore, Frederick S. Kaplan, Martina L. Badell

Bibliographic record

VenueJournal of Clinical Gynecology and Obstetrics · 2015
Typearticle
Languageen
FieldMedicine
TopicHeterotopic Ossification and Related Conditions
Canadian institutionsnot available
Fundersnot available
KeywordsFibrodysplasia ossificans progressivaOsteogenesis imperfectaMedicinePregnancyPediatricsOssificationObstetricsSurgeryPathology

Abstract

fetched live from OpenAlex

Due to advances in neonatal care, prenatal diagnostics, and artificial reproductive techniques, women affected by skeletal disorders now survive into their reproductive years, desire fertility, and become pregnant. Osteogenesis imperfecta (OI) is a disease of brittle bones prone to fracture and is one of the most common of the skeletal dysplasias. Fibrodysplasia ossificans progressiva (FOP) is a rare debilitating genetic condition characterized by congenital malformations of the great toes and progressive, disabling heterotopic ossification (HO) in which bone forms outside of the skeleton. Here we report two cases of viable pregnancies with severe maternal skeletal disorders. This is only the fourth reported case of a viable pregnancy in a woman with FOP. These cases highlight the complexity of caring for women during pregnancy affected by severe skeletal disorders, the formidable risks when these women become pregnancy, and how these high-risk pregnancies can be successfully managed by a collaborative multidisciplinary care team. J Clin Gynecol Obstet. 2015;4(1):184-187 doi: http://dx.doi.org/10.14740/jcgo306w

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)0.005
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 score0.162
Threshold uncertainty score0.615

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.005
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 head0.113
GPT teacher head0.397
Teacher spread0.284 · 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
Published2015
Admission routes1
Has abstractyes

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