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Record W4291736994 · doi:10.1038/s41372-022-01483-6

Epidemiology of post-hemorrhagic ventricular dilatation in very preterm infants

2022· review· en· W4291736994 on OpenAlexaff
Jehier Afifi, Prakesh S. Shah, Xiang Y. Ye, Vibhuti Shah, Bruno Piedbœuf, Keith J. Barrington, Edmond Kelly, Walid El‐Naggar, Marc Beltempo, Jaideep Kanungo, Jonathan Wong, Zenon Cieslak, Rebecca Sherlock, Ayman Abou Mehrem, Jennifer Toye, Khalid Aziz, Joseph Ting, Carlos Fajarado, Jaya Bodani, Lannae Strueby, Mary Seshia, Deepak Louis, Ruben Alvaro, Amit Mukerji, Orlando da Silva, Sajit Augustine, Kyong‐Soon Lee, Brigitte Lemyre, Thierry Daboval, Faiza Khurshid, Victoria Bizgu, Anie Lapointe, Guillaume Éthier, Christine Drolet, Martine Claveau, Marie St‐Hilaire, Valérie Bertelle, Édith Massé, Roderick Canning, Hala Makary, Cecil Ojah, Julie Emberley, Andrzej Kajetanowicz, Shoo K. Lee

Bibliographic record

VenueJournal of Perinatology · 2022
Typereview
Languageen
FieldMedicine
TopicNeonatal and fetal brain pathology
Canadian institutionsJaneway Children's Health and Rehabilitation CentreSaint John Regional HospitalDr. Everett Chalmers Regional HospitalCentre Hospitalier Universitaire de SherbrookeHôpital Maisonneuve-RosemontCentre hospitalier universitaire de QuébecJewish General HospitalKingston General HospitalCape Breton Regional HospitalChildren's Hospital of Eastern OntarioLondon Health Sciences CentreSunnybrook Health Science CentreSt. Boniface HospitalWindsor Regional HospitalHealth Sciences CentreIzaak Walton Killam Health CentreHamilton Health SciencesRoyal Alexandra HospitalB.C. Women's Hospital & Health CentreFoothills Medical CentreSurrey Memorial HospitalVictoria General HospitalHospital for Sick ChildrenRoyal Columbian HospitalUniversity of TorontoRegina General HospitalMcGill University Health CentreMoncton HospitalOttawa HospitalCentre Hospitalier Universitaire Sainte-JustineDalhousie UniversityMontreal Children's HospitalMount Sinai HospitalUniversité LavalAlberta Children's Hospital
Fundersnot available
KeywordsMedicinePediatricsShunt (medical)Incidence (geometry)NeonatologyEpidemiologyGestationIntraventricular hemorrhageGestational ageInternal medicinePregnancy

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.055
GPT teacher head0.362
Teacher spread0.307 · 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 designObservational
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

Citations5
Published2022
Admission routes1
Has abstractno

Explore more

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