Excess molar volumes and refractive indices of binary mixtures of isopropylethanoate and symmetrical hydrocarbons at 308.15 K
Bibliographic record
Abstract
Abstract Densities and refractive indices of binary mixtures of isopropylethanoate with several symmetrical hydrocarbons viz cyclohexane, benzene, 1,4‐dimethylbenzene and 1,3,5‐trimethylbenzene at 308.15 K have been measured. The excess molar volumes (VE) are evaluated from the measured density values for the four binary systems. Experimental refractive indices are used to evaluate deviation in refractive indices (Δn) and molar refraction at experimental temperature. VE values are positive for the mixtures studied except binary mixtures between ester and 1,4‐dimethylbenzene which have negative VE values. Standard deviations σ(VE) and σ(Δn) are also reported. Results are discussed in terms of molecular interactions between the components of the mixtures. Nous avons mesuré les densités et les indices de réfraction de mélanges binaires d'isopropyléthanoate avec plusieurs hydrocarbures symétriques, soit du cyclohexane, du benzène, du 1,4‐diméthylbenzène et du 1,3,5‐triméthylbenzène à 308,15 K. Les volumes molaires excédentaires (VE) ont été évalués à partir des densités mesurées pour les quatre systèmes binaires. Les indices expérimentaux de réfraction ont servi à évaluer l'écart des indices de réfraction (Δn) ainsi que la réfraction molaire à la température expérimentale. Les valeurs des VE étaient positives pour les mélanges étudiés à l'exception des mélanges binaires d'ester et de 1,4‐diméthylbenzène qui présentaient des valeurs des VE négatives. Les écarts type σ(VE) et σ(Δn) sont également indiqués. La discussion des résultats porte sur les interactions moléculaires entre les composants des mélanges. © 2010 Canadian Society for Chemical Engineering
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".