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Record W2463243714 · doi:10.5539/ijc.v8n3p35

Carbonyl Chalcogenides Clusters Existing as Disguised Forms of Hydrocarbon Isomers

2016· article· en· W2463243714 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
KeywordsChemistryHydrocarbonChalcogenideCluster (spacecraft)BoraneCrystallographySimilarity (geometry)MetalStereochemistryOrganic chemistryCatalysis

Abstract

fetched live from OpenAlex

<p>The 4n Series Method has been utilized to categorize, analyze and predict structures for transition metal carbonyl, borane, hydrocarbon and Zintl ion clusters. The method is being extended to study carbonyl chalcogenide clusters. Adequate examples have been given to demonstrate the application of the 4n series method to categorize clusters and where possible predict their possible skeletal structures. In this paper, the method is being applied to the study of carbonyl chalcogenide cluster complexes. What has been found is the striking structural similarity of a wide range of carbonyl chalcogenide clusters to those of corresponding hydrocarbon clusters. It was observed that when a derived hydrocarbon from a cluster, F<sub>CH</sub> = C<sub>n</sub>H<sub>q</sub>, is such that n<q, the cluster portrays structural similarity with an equivalent hydrocarbon. On the other hand when n>q, the ‘hydrocarbon character’ becomes reduced and the typical cluster tendencies increase. When n = q, the situation becomes more or less a borderline case. When q=0, then F<sub>CH</sub> = C<sub>n</sub>. When the series becomes bi-capped or more, then the equivalent carbon cations are obtained.</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)0.001
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 score0.042
Threshold uncertainty score0.468

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.000
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 head0.019
GPT teacher head0.308
Teacher spread0.289 · 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

Citations2
Published2016
Admission routes1
Has abstractyes

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