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Record W2086798344 · doi:10.1021/ci0000474

Benchmarking of Model Core Potentials:  Application to the Halogen Complexes of Group 4 Metals

2000· article· en· W2086798344 on OpenAlexfundno aff
Stephen A. Decker, Mariusz Kłobukowski

Bibliographic record

VenueJournal of Chemical Information and Computer Sciences · 2000
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPseudopotentialHalogenValence electronElectronegativityBond lengthCore electronChemistryAtom (system on chip)MetalComputational chemistryCrystallographyMaterials scienceElectronAtomic physicsPhysicsQuantum mechanicsAlkylOrganic chemistry

Abstract

fetched live from OpenAlex

The reliability of the model core potential (MCP) method was probed in a systematic RHF and MP2 study of the geometries of the group 4 metal halogen complexes (MX4; M = Ti, Zr, Hf and X = F, Cl, Br, I). The computed bond lengths were compared with experimental values, as well as those predicted using effective core potentials. Provided that electrons from the outermost core shell of the metal atom are treated explicitly in the calculation, both the MCP and ECP methods predict M-X bond lengths within 0.02-0.03 A of experiment. The reaction energies for a simple set of halogen substitution reactions of the MX4 complexes leading to the mixed halogen complex, MX2Y2, were also studied. Although no experimental values are available for these reactions, comparison was made with the values computed using effective core potentials. The predictability of the different pseudopotential techniques and the importance of the metal atom valence basis set contraction scheme and polarization space are discussed.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.614
Threshold uncertainty score0.149

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)0.0000.000

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 head0.020
GPT teacher head0.269
Teacher spread0.249 · 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 designSimulation or modeling
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

Citations6
Published2000
Admission routes1
Has abstractyes

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