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Record W2331748055 · doi:10.1055/s-2006-945544

CLASSIFICATION OF CNS MALFORMATIONS

2006· article· en· W2331748055 on OpenAlexaff
H Sarnat, Laura Flores‐Sarnat

Bibliographic record

VenueNeuropediatrics · 2006
Typearticle
Languageen
FieldMedicine
TopicFetal and Pediatric Neurological Disorders
Canadian institutionsAlberta Children's HospitalUniversity of Calgary
Fundersnot available
KeywordsMedicineNeuroscienceClinical neurologyBiology

Abstract

fetched live from OpenAlex

Objective: to find a clinically useful etiological classification of malformations of the CNS that combine traditional morphology with molecular genetics. Introduction: Classification is primordial in organizing thoughts for comparing information and concepts; the process begins soon after birth. The classification of malformations of the brain has undergone many revisions over the years as new data and concepts were discovered, but the most important principles are 1) recognition that all malformations must be viewed in the context of disorders of embryological development, and 2) traditional descriptive morphogenesis of the past centuries must be integrated with recent molecular genetic data about developmental programming. Neither pure morphological schemes nor pure genetic schemes provide full insight into normal and abnormal ontogenesis and its application to clinical care of children with congenital malformations. We propose that malformations be classified into categories as disorders of 1) genetic gradients of expression in the three axes of the neural tube; 2) segmentation of the neural tube; 3) neuroblast migration; 4) cellular lineage; 5) neural tube induction of non-neural tissues: neurocristopathies. Examples: Axes of the Neural Tube: Vertical axis: Overexpression of a dorsalizing or ventralizing gene leads to duplication or hypertrophy of structures; Underexpression results in midline noncleavage or hypoplasia. Longitudinal axis: rostrocaudal gradient: holoprosencephaly with noncleavage of diencephalon and mesencephalon, as well as telencephalon; caudorostral gradient: sacral agenesis. Horizontal axis: mediolateral gradient: holoprosencephaly affecting medial cortex more than lateral cortex; lateromedial gradient: pontocerebellar hypoplasia. Segmentation of the Neural Tube: Agenesis of specific neuromeres: absent midbrain and pons; absent basal ganglia. Ectopic expression: Chiari malformation. Neuroblast migratory disorders: Lissencephalies; pachygyrias; schizencephaly. Disorders of cellular lineage: tuberous sclerosis; hemimegalencephaly. Disorders of neural crest: neural induction of craniofacial structures; neurocutaneous syndromes. Conclusion: The New Neuroembryology is an integration of anatomical morphogenesis and molecular genetic programming that provides insight as an etiological, rather than a purely descriptive, classification of CNS malformations.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.021
GPT teacher head0.241
Teacher spread0.220 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2006
Admission routes1
Has abstractyes

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