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Record W2897403244 · doi:10.1021/acs.inorgchem.8b02314

Estimating the Wavenumber of Terminal Metal-Hydride Stretching Vibrations of Octahedral d<sup>6</sup> Transition Metal Complexes

2018· article· en· W2897403244 on OpenAlexafffund
Robert H. Morris

Bibliographic record

VenueInorganic Chemistry · 2018
Typearticle
Languageen
FieldChemical Engineering
TopicCarbon dioxide utilization in catalysis
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsChemistryOctahedronHydrideTransition metalMetalWavenumberCrystallographyTerminal (telecommunication)VibrationInorganic chemistryCrystal structureOrganic chemistryOpticsPhysics

Abstract

fetched live from OpenAlex

The wavenumbers of 774 terminal hydride infrared active stretching modes of 478 distinct classes of structures of d6 octahedral complexes of Mn(I), Re(I), Fe(II), Ru(II), Os(II), Co(III), Rh(III), Ir(III), and Pt(IV) were collected from the literature. A fair correlation (R2 0.95 with standard deviation 31 cm–1) is found for the data with the equation νMHcalc = ν0 + Δνt + Δνn, where ν0 is the base wavenumber for the metal ion in question, Δνt is the parameter of influence of the ligand trans to the hydride, and Δνn is a correction for the charge of the complex [MHL5]n+. The introduction of a cis influence parameter has little effect on the correlation, showing that the trans influence dominates in this case. The equation is useful in identifying anomalous data reported in the literature, validating future assignments of νMH, understanding better metal-hydride bonding, and possibly assisting in identifying superior hydride-based catalysts.

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 score0.243
Threshold uncertainty score0.967

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.239
Teacher spread0.229 · 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

Citations36
Published2018
Admission routes2
Has abstractyes

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