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Record W3136199572 · doi:10.3390/children8030227

Neuroimaging at Term Equivalent Age: Is There Value for the Preterm Infant? A Narrative Summary

2021· review· en· W3136199572 on OpenAlex
Rudaina Banihani, Judy Seesahai, Elizabeth Asztalos, Paige Church

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueChildren · 2021
Typereview
Languageen
FieldMedicine
TopicNeonatal and fetal brain pathology
Canadian institutionsUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsNeuroimagingMagnetic resonance imagingFunctional magnetic resonance imagingMedicinePopulationNarrative reviewCursePsychologyNeuroscienceIntensive care medicineRadiology

Abstract

fetched live from OpenAlex

Advances in neuroimaging of the preterm infant have enhanced the ability to detect brain injury. This added information has been a blessing and a curse. Neuroimaging, particularly with magnetic resonance imaging, has provided greater insight into the patterns of injury and specific vulnerabilities. It has also provided a better understanding of the microscopic and functional impacts of subtle and significant injuries. While the ability to detect injury is important and irresistible, the evidence for how these injuries link to specific long-term outcomes is less clear. In addition, the impact on parents can be profound. This narrative summary will review the history and current state of brain imaging, focusing on magnetic resonance imaging in the preterm population and the current state of the evidence for how these patterns relate to long-term outcomes.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.980
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.044
GPT teacher head0.342
Teacher spread0.297 · 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