Bibliographic record
Abstract
In organic chemistry, Cahn-Ingold-Prelog (CIP) rules and R and S descriptors are a well-established standard for identifying the stereochemistry of tetrahedral stereocenters. For other molecular geometries, such as the octahedral or bipyramidal geometries regularly observed in organometallic and molecular inorganic chemistry, there are point solutions for specific geometries and compounds classes but there is no systematic generally applicable solution. To overcome this limitation, a new generic stereochemistry descriptor is proposed. This stereodescriptor is independent of the type of molecular geometry (e.g., T-4, OC-6, TBPY-5) and is aimed to support any currently known molecular geometry. It does not require prior knowledge of the the type of molecular geometry, nor does it explicitly determine the molecular geometry. Several geometries and examples are discussed, including complex examples such as multi-substituted ferrocenes and octahedral 'enhanced' stereochemistry, and the new stereodescriptor is compared with the CIP rules. The new stereodescriptor can, for example, form the basis for a future extension of the International Chemical Identifier (InChI) to uneqivocally identify the stereochemistry of organometallics and molecular inorganics.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.009 |
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".