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Record W2988857876 · doi:10.1097/mnh.0000000000000562

Preventing a nonexistent entity

2019· review· en· W2988857876 on OpenAlexaff
Swapnil Hiremath, Juan Carlos Q. Velez

Bibliographic record

VenueCurrent Opinion in Nephrology & Hypertension · 2019
Typereview
Languageen
FieldMedicine
TopicAcute Kidney Injury Research
Canadian institutionsMarch of Dimes Canada
Fundersnot available
KeywordsAcute kidney injuryObservational studyIntensive care medicineMedicineContrast (vision)IsotonicInternal medicineComputer science

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: In recent years, doubt has been cast on the existence of contrast-induced acute kidney injury. The skepticism has stemmed from observational studies from large administrative healthcare databases. Although they correctly call that contrast-induced acute kidney injury is less common than previously thought, they cannot completely exclude selection bias. RECENT FINDINGS: Though less common than previously thought, contrast-induced acute kidney injury still exists. The only prophylactic method that remains valid is that of isotonic volume expansion, which is still deemed beneficial in high-risk patients. N-acetylcysteine and sodium bicarbonate are ineffective and their use should be abandoned. SUMMARY: Contrast-induced kidney injury should be defined based on clinical grounds, not merely on biochemical numbers. More research to validate a clinical definition is necessary in order to accurately re-examine its incidence.

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)0.004
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.015
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.019
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0040.003
Science and technology studies0.0010.002
Scholarly communication0.0030.004
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0150.004

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 head0.294
GPT teacher head0.465
Teacher spread0.171 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2019
Admission routes1
Has abstractyes

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