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Record W1977315639 · doi:10.15420/ecr.2007.0.1.54

Contrast-induced Nephropathy in Coronary Intervention

2007· article· en· W1977315639 on OpenAlexaff
H.P. Niendorf, Philipp Lengsfeld, Matthias Bräutigam

Bibliographic record

VenueEuropean Cardiology Review · 2007
Typearticle
Languageen
FieldMedicine
TopicAcute Kidney Injury Research
Canadian institutionsGlobal Affairs Canada
Fundersnot available
KeywordsContrast-induced nephropathyMedicineCreatinineDialysisNephropathyCardiologyInternal medicineContrast (vision)UrologyEndocrinologyComputer science

Abstract

fetched live from OpenAlex

Contrast-induced nephropathy (CIN) in the actual essence of the term refers to renal damage induced by a contrast medium. The ultimate clinical manifestation of CIN is renal failure requiring dialysis, and this article will concentrate on CIN as a clinical outcome. However, transient rises in serum creatinine have been frequently used as a surrogate marker that is suggested to predict renal failure, and these transient rises are usually also termed CIN.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.043
GPT teacher head0.365
Teacher spread0.322 · 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

Citations0
Published2007
Admission routes1
Has abstractyes

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