Ligand directed self-assembly vs. metal ion coordination algorithm—when does the ligand or the metal take control?
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.
Bibliographic record
Abstract
Polyfunctional hydrazone ligands with multidentate terminal donor groups offer metal ions many donor choices, and the coordination outcome depends mainly on the identity of the metal ion. Co(ii) and Ni(ii) prefer to adopt largely undistorted, six-coordinate geometries, while Cu(ii) can easily adapt to a variety of coordination situations (e.g. CN 4-6), and will optimize its coordination number and stereochemistry based on all the available donors. Ni(ii) and Co(ii) form simple [2 x 2] [M(4)-(micro(2)-O)(4)] square grids with such ditopic hydrazone ligands, and ignore other coordination options, while Cu(ii) tries to bind to all the available donors, and forms extended and 2D structures based on linked Cu(ii) triads rather than grids. Ni(ii) is also reluctant to compromise its desire to maximize its crystal field stabilization energy (CFSE) by binding to 'weak' ligands, and with a tetratopic pyrazole bis-hydrazone ligand it ignores the oxygen donors in favour of nitrogen, forming a novel trinuclear, triangular cluster. Also, reaction of a linear Ni(ii)(3) complex of a tetratopic pyridazine bis-hydrazone ligand with NiN(6) coordination spheres with Cu(ii), leads exclusively to a square Cu(12) grid based complex, and complete displacement of nickel. Structural and magnetic properties are highlighted, and metal-ligand interactions are discussed in detail.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it