Solvent–metal interactions in bis[1,2-dicarba-<i>closo</i>-dodecaboran(12)-1-yl]mercury(II) dichloromethane solvate and bis[1,12-dicarba-<i>closo</i>-dodecaboran(12)-1-yl]mercury(II) tetrahydrofuran solvate
Bibliographic record
Abstract
The title compounds, bis[1,2-dicarba-closo-dodecaboran(12)-1-yl]mercury(II) dichloromethane solvate, [Hg(C(2)B(10)H(11))(2)].CH(2)Cl(2), (I), and bis[1,12-dicarba-closo-dodecaboran(12)-1-yl]mercury(II) tetrahydrofuran solvate, [Hg(C(2)B(10)H(11))(2)].C(4)H(8)O, (II), were prepared in excellent yields using a robust synthetic procedure involving the reaction of HgCl(2) with the appropriate monolithiocarborane. X-Ray analysis of the products revealed strong interactions between the Hg atoms in both complexes and the respective lattice solvent. The distances between the Hg(II) centers and the Cl atoms of the dichloromethane solvent molecule in the ortho-carborane derivative, (I), and the O atom of the tetrahydrofuran molecule in the para-carborane complex, (II), are shorter than the sums of the van der Waals radii for Hg and Cl (3.53 A), and Hg and O (3.13 A), respectively, indicating moderately strong interactions. There are two crystallographically independent molecules in the asymmetric unit of both compounds, which, in each case, are related by differing relative positions of the cages.
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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".