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Record W2789578666 · doi:10.1016/j.jpeds.2017.12.020

Severe Neurodevelopmental Impairment in Neonates Born Preterm: Impact of Varying Definitions in a Canadian Cohort

2018· article· en· W2789578666 on OpenAlexafffundabout
Matthew D. Haslam, Sarka Lisonkova, Dianne Creighton, Paige Church, Junmin Yang, Prakesh S. Shah, K.S. Joseph, Anne Synnes, Adele Harrison, Joseph Ting, Zenon Cieslak, Rebecca Sherlock, Wendy Yee, Carlos Fajardo, Khalid Aziz, Jennifer Toye, Zarin Kalapesi, Koravangattu Sankaran, Sibasis Daspal, Molly Seshia, Ruben Alvaro, Amit Mukerji, Orlando da Silva, Chuks Nwaesei, Kyong‐Soon Lee, Michael Dunn, Brigitte Lemyre, Kimberly Dow, Ermelinda Pelausa, Lajos Kovács, Keith J. Barrington, Christine Drolet, Sean P. Riley, Martine Claveau, Daniel Faucher, Valérie Bertelle, Édith Massé, Roderick Canning, Hala Makary, Cecil Ojah, Luis Monterrosa, Wayne L. Andrews, Akhil Deshpandey, Doug McMillan, Jehier Afifi, Andrzej Kajetanowicz, Shoo K. Lee, Thevanisha Pillay, Reg Sauvé, Leonora Hendson, Amber Reichert, Jaya Bodani, Diane Moddemann, Chukwuma Nwaesei, Thierry Daboval, David Lee, Linh Ly, Edmond Kelly, Salhab el Helou, Françine Lefebvre, Charlotte Demers, Sylvie Bélanger, Michael Vincer, Phil Murphy

Bibliographic record

VenueThe Journal of Pediatrics · 2018
Typearticle
Languageen
FieldMedicine
TopicNeonatal Respiratory Health Research
Canadian institutionsUniversity of TorontoUniversity of CalgaryUniversity of British Columbia
FundersCanadian Institutes of Health ResearchOntario Ministry of Health and Long-Term Care
KeywordsMedicineIncidence (geometry)Gestational agePediatricsCohortBronchopulmonary dysplasiaNeonatal intensive care unitCohort studyPregnancyInternal medicine

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 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.350
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations47
Published2018
Admission routes3
Has abstractno

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