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Record W3212322624 · doi:10.1038/s41372-021-01260-x

Association of early dysnatremia with mortality in the neonatal intensive care unit: results from the AWAKEN study

2021· article· en· W3212322624 on OpenAlexafffund
Abby Basalely, Russell Griffin, Katja M. Gist, Ronnie Guillet, David J. Askenazi, Jennifer R. Charlton, David T. Selewski, Mamta Fuloria, Frederick J. Kaskel, Kimberly J. Reidy, Namasivayam Ambalavanan, Stuart L. Goldstein, Amy T. Nathan, James M. Greenberg, Alison Kent, Jeffrey J. Fletcher, Farah Sethna, Danielle E. Soranno, Jason Gien, Kim Reidy, Natalie Uy, Mary Revenis, Sofia Perrazo, Shantanu Rastogi, George Schwartz, Carl T. D’Angio, Erin Rademacher, Ahmed El Samra, Ayesa Mian, Juan C. Kupferman, Alok Bhutada, Michael Zappitelli, Pia Wintermark, Sanjay Wazir, Sidharth Kumar Sethi, Sandeep Dubey, Maroun J. Mhanna, Deepak Kumar, Rupesh Raina, Susan E. Ingraham, Arwa Nada, Elizabeth Bonachea, Richard Ν. Fine, Robert P. Woroniecki, Shanthy Sridhar, Ayse Ariken, Christopher J. Rhee, Lawrence S. Milner, Alexandra Smith, Julie Nicoletta, Cherry Mammen, Avash Singh, Anne Synnes, Jennifer G. Jetton, Tarah T. Colaizy, Jonathan M. Klein, Patrick D. Brophy, Aftab S. Chishti, Mina Hanna, Carolyn Abitbol, Marissa J. DeFreitas, Shahnaz Duara, Salih Yasin, Subrata Sarker, Craig S. Wong, Amy Staples, Robin K. Ohls, Catherine Joseph, Tara L. DuPont, Jonathan R. Swanson, Matthew W. Harer, Patricio E. Ray, Sangeeta Hingorani, Christine Hu, Sandra E. Juul

Bibliographic record

VenueJournal of Perinatology · 2021
Typearticle
Languageen
FieldMedicine
TopicElectrolyte and hormonal disorders
Canadian institutionsUniversity of British ColumbiaMcGill University
FundersNational Institute of Diabetes and Digestive and Kidney DiseasesCenter for Clinical and Translational Sciences, University of Texas Health Science Center at HoustonSchool of Medicine, University of Alabama at BirminghamGeorgia Clinical and Translational Science AllianceChildren's National HospitalUniversity of RochesterChildren's of AlabamaTexas Children's HospitalMcGill UniversityNational Institutes of HealthCincinnati Children's Hospital Medical CenterNationwide Children's HospitalNational Center for Advancing Translational SciencesTufts Medical CenterUniversity of Miami
KeywordsHypernatremiaMedicineAcute kidney injuryCohortHyponatremiaCohort studyIntensive care medicinePediatricsInternal 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 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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.021
GPT teacher head0.305
Teacher spread0.284 · 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
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

Citations13
Published2021
Admission routes2
Has abstractno

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