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Record W2503062824 · doi:10.1080/1061186x.2016.1221957

Biophysical experiments and simulation in nanoparticle-based drug delivery systems

2016· article· en· W2503062824 on OpenAlex
Jenifer Thewalt, D. Peter Tieleman

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

VenueJournal of drug targeting · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLipid Membrane Structure and Behavior
Canadian institutionsUniversity of CalgarySimon Fraser University
FundersAlberta Innovates - Health SolutionsAlberta Innovates - Technology Futures
KeywordsNanotechnologyNanoparticleDrug deliveryDrugComputer scienceCusp (singularity)Biochemical engineeringChemistryPharmacologyMaterials scienceMedicineEngineeringMathematics

Abstract

fetched live from OpenAlex

We are on the cusp of a new era in therapeutics which will be characterized by drugs that can be individually tailored to a patient to be more effective and less likely to cause side effects. One of the most successful ways to deliver such drugs to the physiological site of interest involves embedding them in lipid nanoparticles. Here we give a brief history of the development of lipid-based drug carriers, emphasizing the role that biophysical characterization played in their development. We further argue that in the future, the revolutionary gain in power of computer simulation techniques will enable researchers to efficiently identify optimal lipid nanoparticle compositions and physical characteristics for experimental validation.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.212

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 head0.009
GPT teacher head0.255
Teacher spread0.246 · 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