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Record W4402348317 · doi:10.1097/nan.0000000000000568

Development of an Evidence-Based List of Non-Antineoplastic Vesicants

2024· article· en· W4402348317 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Infusion Nursing · 2024
Typearticle
Languageen
FieldMedicine
TopicChemotherapy-related skin toxicity
Canadian institutionsNickel Institute
Fundersnot available
KeywordsRisk stratificationExtravasationMedicineIntensive care medicineInternal medicinePathology

Abstract

fetched live from OpenAlex

Infiltration of a vesicant, called extravasation, can result in severe patient injuries. Recognition of vesicants and their relative risk of injury is essential to extravasation prevention, early recognition, and appropriate treatment. In this article, the Vesicant Task Force (VTF) updates the previously published Infusion Nurses Society (INS) vesicant list from 2017. The 2024 INS list diverges from earlier vesicant lists, such as the 2017 VTF list, by adopting a risk stratification approach based upon documented patient outcomes, in contrast to the reliance on expert consensus or only surrogate risk indicators, such as pH and osmolarity. The methodology used to create the updated list is explained, and the criteria for high- and moderate-risk vesicants and cautionary vesicants are defined.

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.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.127
Threshold uncertainty score0.367

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.033
GPT teacher head0.347
Teacher spread0.314 · 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