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Record W2325189213 · doi:10.1515/revic-2013-0010

Platinum organometallic complexes: classification and analysis of crystallographic and structural data for dimeric complexes

2013· article· en· W2325189213 on OpenAlexaff
Milan Melnı́k, Peter Mikuš, Clive Edward Holloway

Bibliographic record

VenueReviews in Inorganic Chemistry · 2013
Typearticle
Languageen
FieldChemistry
TopicOrganometallic Complex Synthesis and Catalysis
Canadian institutionsYork University
Fundersnot available
KeywordsChemistryPlatinumCrystallographyOctahedronBond lengthValence (chemistry)Trigonal bipyramidal molecular geometryStereochemistryCrystal structureCatalysis

Abstract

fetched live from OpenAlex

Abstract This review covers over 260 examples of dimeric organoplatinum complexes. Platinum is predominantly found in the oxidation states +2 and +4, but with some examples of 0, +1, +2.5, +3, and of mixed-valence as well. A number of coordination state geometries are observed, of which the most common is essentially square-planar at Pt(II), a distorted octahedral at Pt(IV), and some examples of trigonal planar and trigonal bipyramidal as well. The most common ligands are methyl (Me), carbonyl and PX 3 . The shortest Pt-Pt bond distance is 245.1(1) pm. The mean Pt-Pt bond distance increases in the order: 261.1 pm [Pt(2.5)-Pt(2.5)]<261.3 pm [Pt(III)-Pt(III)]<262.4 pm [Pt(I)-Pt(I)]<270.3 pm [Ot(II)-Pt(II)]<277.2 pm [Pt(0)-Pt(0)]<282.6 pm [Pt(II)-Pt(II)]. The Pt…Pt no-bonding distances are: Pt(II)…Pt(II), 3.008–17.959 pm; Pt(IV)…Pt(IV), 327.5–768.0 pm; Pt(II)-Pt(0), 378.6 pm and Pt(II)…Pt(IV), 389 pm. There are several relationships pointed out between the Pt-Pt distances, Pt-X-Pt bridge angles and covalent radii of coordinated atoms. Several examples contain two crystallographically independent molecules within the same crystal, differing mostly by degree of distortion, which are examples of distortion isomerism.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.868
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0120.000

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 head0.048
GPT teacher head0.282
Teacher spread0.234 · 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.

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

Citations3
Published2013
Admission routes1
Has abstractyes

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