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Record W2480401582 · doi:10.5539/ijc.v8n3p62

The Application of the 4n Series Method to Categorize Metalloboranes

2016· article· en· W2480401582 on OpenAlexvenueno aff
Enos Masheija Rwantale Kiremire

Bibliographic record

VenueInternational Journal of Chemistry · 2016
Typearticle
Languageen
FieldMedicine
TopicBoron Compounds in Chemistry
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryBoranesSeries (stratigraphy)StereochemistryCrystallographyBoronOrganic chemistry

Abstract

fetched live from OpenAlex

<p>Metalloboranes have been categorized by using 4n series method. More than one hundred metalloboranes have been analyzed and characterized by the method. The clusters have been found to be centered within the series range S = 4n+6 to 4n-8. According to the classification, the clusters of series S= 4n+0 are mono-capped, S = 4n-2, bi-capped, S = 4n-4, tri-capped, S = 4n-6, tetra-capped and S= 4n-8, penta-capped. Whereas the known stable boranes have almost non-existent capped boranes, such clusters are prevalent within metalloborane complexes. This implies that metal fragments have the potency of stabilizing the fragile capped boranes.</p>

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.280
Threshold uncertainty score0.163

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.010
GPT teacher head0.323
Teacher spread0.313 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations15
Published2016
Admission routes1
Has abstractyes

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