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Record W2883018826 · doi:10.1002/ajmg.c.31623

Neuropathology of holoprosencephaly

2018· review· en· W2883018826 on OpenAlexaff
Catherine Fallet‐Bianco

Bibliographic record

VenueAmerican Journal of Medical Genetics Part C Seminars in Medical Genetics · 2018
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHedgehog Signaling Pathway Studies
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsHoloprosencephalyNeuropathologyForebrainNeurosciencePhenotypeBiologyPathologyMedicineCentral nervous systemDiseaseFetusGenetics

Abstract

fetched live from OpenAlex

Holoprosencephaly (HPE) is a primary disorder of neural induction and patterning of the rostral neural tube resulting in noncleavage of the forebrain with failure to form two separate distinct hemispheres. The spectrum of HPE is very broad and encompasses various neuropathological phenotypes of different severity. The recent literature has demonstrated that the phenotypic variability of HPE ranges from aprosencephaly-atelencephaly, at the most severe end, to milder forms such as the "middle interhemispheric variant" of HPE at the less severe end of the spectrum. Between them, different intermediate forms demonstrate a continuum in a wide phenotypic spectrum rather than well-defined categories. Although the term "HPE" suggests a disorder affecting only the prosencephalon, other brain structures are involved, underlining the complexity of the malformation. Because of close spatiotemporal interactions and common signaling pathways contributing to the development of both brain and face, concomitant facial and ocular anomalies are associated with brain malformation. In this review, the characteristic neuropathological features of the various forms of HPE are described as well as their associated brain, face, and ocular malformations, to delineate the different phenotypes.

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)0.006
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.992
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.001
Science and technology studies0.0000.005
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0010.002
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 head0.032
GPT teacher head0.368
Teacher spread0.336 · 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 designOther design
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

Citations34
Published2018
Admission routes1
Has abstractyes

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