Cover Picture: Coordination Algorithms Control Molecular Architecture: [Cu<sup>I</sup><sub>4</sub>(L2)<sub>4</sub>]<sup>4+</sup> Grid Complex Versus [M<sup>II</sup><sub>2</sub>(L2)<sub>2</sub>X<sub>4</sub>]<sup>y+</sup> Side‐By‐Side Complexes (M=Mn, Co, Ni, Zn; X=Solvent or Anion) and [Fe<sup>II</sup>(L2)<sub>3</sub>][Cl<sub>3</sub>Fe<sup>III</sup>OFe<sup>III</sup>Cl<sub>3</sub>] (Chem. Eur. J. 16/2003)
Bibliographic record
Abstract
Abstract The cover picture shows how differing coordination algorithms control the molecular architecture of complexes of the pyridazine‐containing, two‐armed, acyclic Schiff base ligand L2 (left, prepared from one equivalent of 3,6‐diformylpyridazine and two equivalents of d‐anisidine). Two very different complexes of L2 self‐assemble from tetrahedral copper(I) versus octahedral zinc(II), nickel(II), and cobalt(II) controlled 1 : 1 reactions with L2. In both cases the metal ions are bridged by the pyridazine moieties in L2, but in the case of the tetrahedral copper(II) the result is a tetrametallic [2×2] grid complex ([CuI4(L2)4]4+: top right), whilst in the case of the octahedral metal(II) ions dimetallic side‐by‐side complexes, [MII2(L2)2(X)4]y+ (M = Mn, Co, Ni, Zn; X = solvent or anion), are formed (bottom right). The cover image was kindly generated by M. Crawford (University of Otago) with Strata Studio Pro (Strata). More details are given by S. Brooker and co‐workers on p. 3772 ff.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.050 | 0.004 |
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".