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Record W2095274433 · doi:10.1021/op060073o

Measurement and Prediction of Solubility of Paracetamol in Water−Isopropanol Solution. Part 1. Measurement and Data Analysis

2006· article· en· W2095274433 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

VenueOrganic Process Research & Development · 2006
Typearticle
Languageen
FieldMaterials Science
TopicCrystallization and Solubility Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsSolubilityGravimetric analysisChemistryAqueous solutionChemometricsChromatographyAnalytical Chemistry (journal)Organic chemistry

Abstract

fetched live from OpenAlex

An attempt has been made to measure the concentration of paracetamol (98%, Aldrich Chemical Co. Inc., MO) in different solutions using an in situ ATR-FTIR device and chemometrics. A partial least-squares (PLS1) algorithm has been applied to construct two calibration models for paracetamol concentration, water mass percent, and temperature. The models and errors have been analyzed using validation data sets and diagnostic tools. The models are then used to evaluate the solubility of paracetamol (PA) in pure isopropanol, pure water, and isopropanol−water mixtures in the temperature range 5−40 °C. The solubility of paracetamol in isopropanol−water mixtures shows a maximum at almost 20 water mass percent. For some selected data points, the measured solubility by the FTIR is in good agreement with the corresponding solubility measured using the gravimetric method. Also the solubility in pure isopropanol and water is in reasonable agreement with the data reported in the literature.

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)0.009
metaresearch head score (Gemma)0.001
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 score0.202
Threshold uncertainty score0.448

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.142
GPT teacher head0.339
Teacher spread0.198 · 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