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Record W2103082926 · doi:10.1136/bcr-2014-207501

A fourth case of Feingold syndrome type 2: psychiatric presentation and management

2014· review· en· W2103082926 on OpenAlexaff
Hooman Ganjavi, Victoria Mok Siu, Marsha Speevak, Penny A. MacDonald

Bibliographic record

VenueBMJ Case Reports · 2014
Typereview
Languageen
FieldMedicine
TopicEsophageal and GI Pathology
Canadian institutionsUniversity of TorontoWestern University
Fundersnot available
KeywordsMicrocephalyMedicineShort statureAnal atresiaIntellectual disabilityPediatricsDuodenal atresiaPresentation (obstetrics)Rare diseaseGeneticsPsychiatryAtresiaDiseasePathologyInternal medicineBiologySurgery

Abstract

fetched live from OpenAlex

Feingold syndrome (FGLDS1) is an autosomal dominant disorder caused by mutations in the MYCN oncogene on the short arm of chromosome 2 (2p24.1). It is characterised by microcephaly, digital abnormalities, oesophageal and duodenal atresias, and often learning disability or mental retardation. In 2011, individuals sharing the skeletal abnormalities of FGLDS1 but lacking mutations in MYCN, were found to harbour hemizygous deletions of the MIR17HG gene on chromosome 13q31.3. These individuals share many of the characteristics of FGLDS1 except for gastrointestinal atresia. The condition was termed Feingold syndrome type 2 (FGLDS2). We describe the presentation and management of a fourth known case of FGLDS2 in an 18-year-old girl with microcephaly, short stature, mildly dysmorphic features, digital malformations and significant cognitive and psychiatric symptoms. Comparative genomic hybridisation array testing confirmed a 7.4 Mb microdeletion in chromosome region 13q31.1q.31.3 corresponding to the MIR17HG gene.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.045
GPT teacher head0.389
Teacher spread0.344 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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

Citations13
Published2014
Admission routes1
Has abstractyes

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