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Record W4400039451 · doi:10.1016/j.cis.2024.103244

Review of ionic liquid and ionogel-based biomaterials for advanced drug delivery

2024· review· en· W4400039451 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAdvances in Colloid and Interface Science · 2024
Typereview
Languageen
FieldChemical Engineering
TopicIonic liquids properties and applications
Canadian institutionsUniversity of Alberta
FundersCanada Research ChairsUniversity of Alberta
KeywordsDrug deliveryNanotechnologyIonic liquidDrugMicelleMaterials scienceChemistryOrganic chemistryPharmacologyAqueous solutionMedicine

Abstract

fetched live from OpenAlex

Ionic liquids (ILs) play a crucial role in the design of novel materials. The ionic nature of ILs provides numerous advantages in drug delivery, acting as a green solvent or active ingredient to enhance the solubility, permeability, and binding efficiency of drugs. They could also function as a structuring agent in the development of nano/micro particles for drug delivery, including micelles, vesicles, gels, emulsion, and more. This review summarize the ILs and IL-based gel structures with their advanced drug delivery applications. The first part of review focuses on the role of ILs in drug formulation and the applications of ILs in drug delivery. The second part of review offers a comprehensive overview of recent drug delivery applications of IL-based gel. It aims to offer new perspectives and attract more attention to open up new avenues in the biomedical applications of ILs and IL-based gels.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.812
Threshold uncertainty score0.759

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.020
GPT teacher head0.350
Teacher spread0.330 · 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