Obtaining accurate chemical shifts for all magnetic nuclei (<sup>1</sup>H, <sup>13</sup>C, <sup>17</sup>O, and <sup>27</sup>Al) in tris(2,4-pentanedionato-<i>O</i>,<i>O</i>′)aluminium(III) — A solid-state NMR case study
Bibliographic record
Abstract
We report a complete set of high-resolution solid-state NMR spectra for all magnetic nuclei (1H, 13C, 17O, and 27Al) in the α-form of tris(2,4-pentanedionato-O,O′)aluminium(III), α-Al(acac)3. These high-resolution NMR spectra were obtained by using a host of solid-state NMR techniques: standard cross-polarization under the magic-angle spinning (CPMAS) method for 13C, 1-D homonuclear decoupling using the windowed DUMBO sequence for 1H, double-rotation (DOR) for 17O and 27Al, and multiple-quantum MAS for 27Al. Some experiments were performed at multiple magnetic fields. We show that the isotropic chemical shifts obtained for 1H, 13C, 17O, and 27Al nuclei in α-Al(acac)3 are highly resolved and accurate, regardless of the nature of the targeted nuclear spins (i.e., spin-1/2 or quadrupolar) and, as such, can be treated equally in comparison with computational chemical shifts obtained from a gauge-including projector-augmented wave (GIPAW) plane-wave pseudopotential DFT method.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".