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Record W2131566674 · doi:10.4103/0975-7406.76463

Differential scanning calorimetry: An invaluable tool for a detailed thermodynamic characterization of macromolecules and their interactions

2011· article· en· W2131566674 on OpenAlexaff
ElmarJ Prenner, MichaelH Chiu

Bibliographic record

VenueJournal of Pharmacy And Bioallied Sciences · 2011
Typearticle
Languageen
FieldChemistry
Topicthermodynamics and calorimetric analyses
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsDifferential scanning calorimetryThermotropic crystalDrug deliveryMacromoleculeExcipientCharacterization (materials science)ChemistryDrugLiposomeNanotechnologyMaterials sciencePhase (matter)ChromatographyPharmacologyOrganic chemistryBiochemistryMedicineThermodynamicsPhysics

Abstract

fetched live from OpenAlex

Differential Scanning Calorimetry (DSC) is a highly sensitive technique to study the thermotropic properties of many different biological macromolecules and extracts. Since its early development, DSC has been applied to the pharmaceutical field with excipient studies and DNA drugs. In recent times, more attention has been applied to lipid-based drug delivery systems and drug interactions with biomimetic membranes. Highly reproducible phase transitions have been used to determine values, such as, the type of binding interaction, purity, stability, and release from a drug delivery mechanism. This review focuses on the use of DSC for biochemical and pharmaceutical applications.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.054
GPT teacher head0.304
Teacher spread0.251 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations362
Published2011
Admission routes1
Has abstractyes

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