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Record W2404301061 · doi:10.1021/acs.jced.5b00667

Solubility Measurement and Simulation of Rivaroxaban (Form I) in Solvent Mixtures from 273.15 to 323.15 K

2015· article· en· W2404301061 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.

Bibliographic record

VenueJournal of Chemical & Engineering Data · 2015
Typearticle
Languageen
FieldMaterials Science
TopicCrystallization and Solubility Studies
Canadian institutionsWestern UniversityUniversity of Toronto
FundersScience and Technology Commission of Shanghai MunicipalityNatural Science Foundation of Jiangsu ProvinceNational Natural Science Foundation of ChinaDeutsche Forschungsgemeinschaft
KeywordsNon-random two-liquid modelSolubilitySolventChemistryMethanolThermodynamicsEthanolChromatographyOrganic chemistryAqueous solutionActivity coefficient

Abstract

fetched live from OpenAlex

The solubility of active pharmaceutical ingredients in various solvents is crucial to their industrial production and the development to final formulations. In this work, the solubility of rivaroxaban (form I) in the binary solvent mixtures of 1-methyl-2-pyrrolidinone with water, methanol, ethanol, and isopropanol from 273.15 to 323.15 K has been experimentally measured. Meanwhile, the dependence of the measured solubility on the temperature as well as on the composition of solvent mixtures has been simulated by Jouyban-Acree (JA) and nonrandom two liquid (NRTL) equations, respectively. The results show that as to the solubility simulation of the studied system JA and NRTL give average relative deviations of 0.1081 and 0.1064, respectively, suggesting that both JA and NRTL can act as an efficient simulation tool for the solubility of rivaroxaban (form I) in pure and mixture solvents at various temperatures.

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)0.002
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 score0.190
Threshold uncertainty score0.334

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.086
GPT teacher head0.301
Teacher spread0.215 · 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