Extraction of Several Divalent Metal Picrates by 18-Crown-6 Ether Derivatives into Benzene: A Refinement of Methods for Analyzing Extraction Equilibria
Bibliographic record
Abstract
Three kinds of extraction constants, Kex, Kex±, and Kex+, were evaluated from the improved model that the following three component-equilibria were added to a previously-proposed model for an overall extraction: M2+ + A-===MA+, MLA+Bz + A-Bz===MLA2,Bz, and A-===A-Bz. Here, Kex, Kex±, and Kex+ were defined as [MLA2]Bz/([M2+][L]Bz[A-]2), [MLA+]Bz[A-]Bz/([M2+][L]Bz[A-]2), and [MLA+]Bz/([M2+][L]Bz[A-]), respectively; the subscript “Bz” denotes benzene as an organic phase. The symbols correspond to M2+ = Ca2+ and Pb2+, L = 18-crown-6 ether (18C6) and dibenzo-18C6 (DB18C6), and A- = picrate ion. The ion-pair formation constant for M2+ + A-===MA+ at M2+ = Pb2+ in an aqueous phase was also determined at 298 K and ionic strength of zero by an extraction of HA into 1,2-dichloroethane and Bz with the presence of Pb2+ in the aqueous phase. The Kex values re-evaluated from the present model were in agreement with those determined by the previous extraction model. Individual distribution constants of A- into Bz were almost constant irrespective of kinds of M2+ and L employed. Furthermore, the composition-determination method of the ion pairs, MLA2, extracted into Bz was re-examined. Similar analyses were performed in the SrA2-, BaA2-18C6, and SrA2-DB18C6 systems without considering the formation of MA+ in the aqueous phases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.002 | 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 teacher head, 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".