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Record W4394884427 · doi:10.1053/j.ajkd.2024.03.013

Association of Blood Mitochondrial DNA Copy Number With Risk of Acute Kidney Injury After Cardiac Surgery

2024· letter· en· W4394884427 on OpenAlexafffund
Vasantha Jotwani, Heather Thiessen‐Philbrook, Dan E. Arking, Stephanie Yang, Eric McArthur, Amit X. Garg, Ronit Katz, Gregory J. Tranah, Joachim H. Ix, Steve Cummings, Sushrut S. Waikar, Mark J. Sarnak, Michael G. Shlipak, Samir M. Parikh, Chirag R. Parikh

Bibliographic record

VenueAmerican Journal of Kidney Diseases · 2024
Typeletter
Languageen
FieldMedicine
TopicAcute Kidney Injury Research
Canadian institutionsWestern UniversityLondon Health Sciences CentreLawson Health Research Institute
FundersNational Heart, Lung, and Blood InstituteSchool of Medicine, Johns Hopkins UniversityUniversidad ICESIMohapatra Family FoundationCareDxInstitute for Clinical Evaluative SciencesBaxter InternationalLawson Health Research InstituteVeterans Affairs San Diego Healthcare SystemLondon Health Sciences CentreSchulich School of Medicine and DentistryUniversity of WashingtonJohns Hopkins UniversityUniversity of California, San DiegoU.S. Department of Veterans AffairsSchool of Medicine, Boston UniversityNational Center for Advancing Translational SciencesSchulich School of Medicine and Dentistry, Western UniversityMinistry of Long-Term CareNational Institute of Diabetes and Digestive and Kidney DiseasesSanofiAkebia TherapeuticsTufts Medical CenterAmerican Kidney FundAmerican Society of NephrologyAstellas Pharma CanadaPKD FoundationNational Institutes of HealthKementerian Kesihatan MalaysiaNateraEmory UniversityEli Lilly and CompanyNational Institute on AgingMinistry of Health, Ontario
KeywordsMedicineAcute kidney injuryKidney diseaseKidneyPathophysiologyRenal functionInternal medicineDiseaseMitochondrionBioinformaticsBiology

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)0.007
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: none
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.005
GPT teacher head0.268
Teacher spread0.263 · 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

Citations6
Published2024
Admission routes2
Has abstractno

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