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Record W4416355014 · doi:10.1093/ndt/gfaf251

Nephrotoxicity of conventional chemotherapeutics: part 1—platinum compounds and antimetabolite agents

2025· article· en· W4416355014 on OpenAlexaff
Adam Kelly, Sourabh Sharma, Omar Mamlouk, Mohamed Hassanein, Raad Chowdhury, Shruti Gupta, Heather Troung, Marco Bonilla, Kartik Kalra, Rimda Wanchoo, Tanazul T. Pariswala, Anna-Eve Turcotte, Ishaan Zaveri, Carl Dernell, Mohamed Ibrahim, Sylvia S Eskander, Prakash Gudsoorkar, Kenar D. Jhaveri, Mark A. Perazella, Paul Hanna

Bibliographic record

VenueNephrology Dialysis Transplantation · 2025
Typearticle
Languageen
FieldMedicine
TopicChemotherapy-induced organ toxicity mitigation
Canadian institutionsCentre Hospitalier Universitaire de Sherbrooke
Fundersnot available
KeywordsAntimetaboliteNephrotoxicityKidneyChemotherapyKidney diseaseChemotherapeutic drugs

Abstract

fetched live from OpenAlex

Anticancer therapies have significantly improved survival rates in patients with cancer; however, despite prophylactic measures, many conventional chemotherapeutic agents cause acute and chronic kidney injury. This review provides a comprehensive analysis of the incidence, characteristics and management of platinum-based and antimetabolite chemotherapeutic agent-associated nephrotoxicity based on the existing literature. Understanding the profiles of these onconephrotoxic agents is essential for optimizing anticancer treatment while minimizing kidney complications.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.412
Threshold uncertainty score0.767

Codex and Gemma teacher scores by category

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

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 head0.015
GPT teacher head0.279
Teacher spread0.264 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations1
Published2025
Admission routes1
Has abstractyes

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