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Record W4406021798 · doi:10.1007/978-3-031-55972-3_1

Introduction on Development, Maturation, and Vulnerability of the Neonatal Brain and Factors Contributing to Injury

2024· book-chapter· en· W4406021798 on OpenAlexaff
Gerda van Wezel‐Meijler, Khorshid Mohammad

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldMedicine
TopicNeonatal and fetal brain pathology
Canadian institutionsAlberta Children's Hospital
FundersGenesis Research Trust
KeywordsBrain developmentNeuroscienceVulnerability (computing)MedicinePsychologyComputer scienceComputer security

Abstract

fetched live from OpenAlex

Abstract The newborn brain is still very immature and undergoes rapid and essential changes. These changes include impressive growth, gyration, and sulcation (folding of the brain surface), myelination (the formation of an insulating layer around the nerve cell extensions), and the formation and pruning of connections between nerve cells and between brain structures. Because of this rapid brain development, the newborn brain is vulnerable to injury. This is especially true for babies born too early (preterm, prematurely), as many brain maturational processes that normally take place within the protective environment of the womb need to take place in an extra-uterine hospital environment.

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)0.000
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.030
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0300.008

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 head0.011
GPT teacher head0.252
Teacher spread0.240 · 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
Published2024
Admission routes1
Has abstractyes

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