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Record W3208681660 · doi:10.1002/pi.6320

The unexplored potential of gas‐responsive polymers in drug delivery: progress, challenges and outlook

2021· article· en· W3208681660 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

VenuePolymer International · 2021
Typearticle
Languageen
FieldMedicine
TopicInhalation and Respiratory Drug Delivery
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNanomedicineNanotechnologyDrug deliveryDrugBiochemical engineeringMaterials scienceChemistryNanoparticlePharmacologyMedicineEngineering

Abstract

fetched live from OpenAlex

Abstract Targeted drug delivery based on polymeric nanoparticles has been a long‐standing interest in nanomedicine for its beneficial traits including controlled and localized drug release. Gas‐responsive polymers offer an advantageous platform and have been slowly gaining attention in spatially locating and displaying unique interactions of specific responsive chemical entities in polymeric chains with endogenous gaseous stimuli. In this review, we highlight recent developments in polymeric nanoformulations with stimulant chemical entities for gasotransmittors such as NO, CO, H 2 S, SO 2 , O 2 and CO 2 in enhancing efficacy in therapeutic interventions. We underline some challenges and limitations of exploring these systems for clinical applications, and how we can further tap into the potential of these emerging materials. © 2021 Society of Industrial Chemistry.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.899
Threshold uncertainty score0.310

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 head0.261
Teacher spread0.245 · 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