MétaCan
Menu
Back to cohort
Record W4399766042 · doi:10.32920/26052835

Characterization of Liposomal Release Temperature Using a Low Field Magnetic Resonance System

2024· preprint· en· W4399766042 on OpenAlex
Khalid Noori

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

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicFiber-reinforced polymer composites
Canadian institutionsToronto Metropolitan UniversityWestern University
Fundersnot available
KeywordsCharacterization (materials science)Field (mathematics)LiposomeMaterials scienceNuclear magnetic resonanceNanotechnologyPhysicsMathematics

Abstract

fetched live from OpenAlex

<p>The use of liposomes as chemotherapeutic carriers has been the subject of many research studies, with emphasis on enhancing the therapeutic index by increasing effect on cancer cells and reducing side effects. An important parameter to characterize for thermosensitive liposomes, TSLs, is the release temperature, Tr, the temperature at which liposomes release most of their content. By loading liposomes with a contrast agent such as Mn2+, a benchtop NMR system can be used to determine Tr through incremental heating. In this work, the release temperature was extracted from relaxometry measurements of Mn2+-loaded TSLs. Tr values were then compared with transition temperature values, Tm, the temperature at which liposomes’ bilayer changes state, obtained by a standard technique. The difference of the average values between Tr and Tm was approximately 0.5 oC. The discrepancy is due to artifacts produced by the standard technique. Nonetheless, Tm can be used to predict Tr.</p>

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 categoriesMeta-epidemiology (narrow)
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 score0.429
Threshold uncertainty score1.000

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 integrity0.0000.001
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 head0.004
GPT teacher head0.187
Teacher spread0.182 · 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

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same topicFiber-reinforced polymer compositesFrench-language works237,207