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Record W2889139728 · doi:10.1016/j.pedneo.2018.08.008

Conventional MRI combined with DTI for neonatal hyperbilirubinemia; Methodological issues on diagnostic value

2018· letter· en· W2889139728 on OpenAlexaboutno aff
Siamak Sabour, Hadis Batari

Bibliographic record

VenuePediatrics & Neonatology · 2018
Typeletter
Languageen
FieldMathematics
TopicStatistical Methods in Epidemiology
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDiffusion MRIFractional anisotropyGlobus pallidusMagnetic resonance imagingInternal capsuleNuclear medicinePediatricsInternal medicineRadiologyBasal gangliaWhite matterCentral nervous system

Abstract

fetched live from OpenAlex

We read with interest the article by Yan R and colleagues published in the April 2018 issue of Pediatr Neonatol.1 Increased signal intensity in the globus pallidus on MR T1WI is an important sign of neonatal bilirubin encephalopathy. Brain diffusion tensor imaging (DTI) has not been used extensively to study hyperbilirubinemia (HB). The purpose of the authors was to evaluate the diagnostic value of conventional magnetic resonance imaging (MRI) combined with DTI (MRI-DTI) in neonatal hyperbilirubinemia.

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)0.097
metaresearch head score (Gemma)0.299
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.097
Threshold uncertainty score0.514

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0970.299
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0050.003
Science and technology studies0.0010.003
Scholarly communication0.0040.003
Open science0.0040.002
Research integrity0.0030.003
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 head0.188
GPT teacher head0.444
Teacher spread0.256 · 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 designTheoretical or conceptual
Domainnot available
GenreCommentary

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
Published2018
Admission routes1
Has abstractyes

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