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Record W2277784009 · doi:10.1007/s12630-014-0302-y

Interrelationship of preoperative anemia, intraoperative anemia, and red blood cell transfusion as potentially modifiable risk factors for acute kidney injury in cardiac surgery: a historical multicentre cohort study

2014· article· en· W2277784009 on OpenAlexafffund
Keyvan Karkouti, Hilary P. Grocott, Richard Hall, Michael E. Jessen, Cornelis Kruger, Adam Lerner, Charles MacAdams, C. David Mazer, Étienne de Médicis, Paul S. Myles, Fiona E. Ralley, Michel Rheault, Antoine Rochon, Mark S. Slaughter, Andrew Sternlicht, Summer Syed, Terrence Waters

Bibliographic record

VenueCanadian Journal of Anesthesia/Journal canadien d anesthésie · 2014
Typearticle
Languageen
FieldMedicine
TopicBlood transfusion and management
Canadian institutionsUniversité de MontréalUniversité LavalLondon Health Sciences CentreUniversity of British ColumbiaMontreal Heart InstituteCentre Hospitalier Universitaire de SherbrookeUniversity of TorontoWestern UniversitySt. Michael's HospitalVancouver General HospitalUniversity of CalgaryFoothills Medical CentreInstitut universitaire de cardiologie et de pneumologie de QuébecUniversity of ManitobaHamilton Health SciencesDalhousie UniversityMcMaster UniversityToronto General HospitalUniversity Health NetworkQueen Elizabeth II Health Sciences Centre
FundersUniversity of TorontoUniversity of Manitoba
KeywordsMedicineAnemiaAcute kidney injuryCardiac surgeryBlood transfusionCardiopulmonary bypassHemoglobinSurgeryAnesthesiaInternal 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)0.003
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 score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.009
GPT teacher head0.225
Teacher spread0.215 · 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

Citations167
Published2014
Admission routes2
Has abstractno

Explore more

Same venueCanadian Journal of Anesthesia/Journal canadien d anesthésieSame topicBlood transfusion and managementFrench-language works237,207