The Main Group Elements, Fragments, Compounds and Clusters Obey the 4n Rule and Form 4n Series: They are Close relatives to Transition Metal Counterparts via the 14n Linkage
Bibliographic record
Abstract
The paper presents numbers which were derived from 4n-based series in a matrix table. The numbers agree precisely with the total number of valence electrons surrounding the respective skeletal elements. The series approach focuses mainly on the number of skeletal elements and their respective number of valence electron content regardless of the origin of the electrons and the type of skeletal elements. For instance, any 6 skeletal elements of transition metal carbonyls surrounded by 86 valence electrons coded as (6,86), series S = 14n+2 normally adopt an octahedral geometry whereas (6,26) series S = 4n+2 for main group elements also tend to adopt an octahedral shape. The transition metal carbonyl cluster series were extensively covered in our previous articles. This paper demonstrates that the main group fragments, clusters and molecules which we normally explain by terms such as valency, valence electrons and octet rule also obey the 4n-based series. The fragments, molecules and clusters of the main group elements correspond well to those of respective transition metal clusters especially the carbonyls if the masking electrons are removed from them. Hence, the series approach is a qualitative method that acts as a unifier of some transition metal clusters with some main group elements clusters.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".