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Record W2013824468 · doi:10.1139/v05-257

Prediction of the photoelectron spectrum for XPY<sub>2</sub> (X = H, F, Cl; Y = O, S) type of molecules by ab initio and DFT methods

2006· article· en· W2013824468 on OpenAlexvenueno aff
Didier Bégué, Jean‐Marc Sotiropoulos, Claude Pouchan, Daisy Y Zhang

Bibliographic record

VenueCanadian Journal of Chemistry · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsnot available
Fundersnot available
KeywordsChemistryAb initioIonization energyDensity functional theoryAtomic physicsMoleculeValence (chemistry)Molecular orbitalIonizationComputational chemistryElectron affinity (data page)PhysicsIon

Abstract

fetched live from OpenAlex

The present study reports the theoretical vertical ionization potentials (IPs) for all the valence electrons in six XPY2 molecules by utilizing the corrected orbital energies calculated with three theoretical methods, namely, the ab initio Hartree–Fock (HF), and both the pure and hybrid density functional theory (DFT) methods at, respectively, the BLYP/6-311+G* and B3lYP/6-311+G* levels of theory. Evaluation of the numerical corrections to the orbital energies was achieved by comparisons with the IP values obtained via explicit computation of the energy differences between the neutral molecules and the corresponding radical cations (the ΔSCF method) and shows values from –0.9 to –1.9 eV for the HF, and positive values from 2.9 to 3.9 eV and from 1.8 to 2.4 eV for the pure and hybrid DFT methods, respectively. In contrast to the orbital energies, the ΔSCF method is shown to give consistent values among the three methods, as well as reasonable agreement with the experimental IP values.Key words: ionization potential, phosphorane, Koopmans' theorem, Janak's theorem.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.009
GPT teacher head0.234
Teacher spread0.225 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2006
Admission routes1
Has abstractyes

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Same venueCanadian Journal of ChemistrySame topicAdvanced Chemical Physics StudiesFrench-language works237,207