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Record W1579049348 · doi:10.1063/1.2264331

Decay dynamics of the long-range H¯Σg+1 state of D2 and H2: Experiment and theory

2006· article· en· W1579049348 on OpenAlexaff
Stephen C. Ross, Toshio Yoshinari, Yoshihiro Ogi, Koichi Tsukiyama∥

Bibliographic record

VenueThe Journal of Chemical Physics · 2006
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsRotational–vibrational spectroscopyAutoionizationExcited stateAtomic physicsKinetic isotope effectRange (aeronautics)Quantum tunnellingChemistryIonIsotopePhysicsQuantum mechanicsIonizationMaterials scienceDeuterium

Abstract

fetched live from OpenAlex

We present accurate experimental measurements of the lifetimes of rovibrational levels of the long-range H1Sigmag+ state for both D2 and H2, obtained directly from the observation of the time-dependent decay of the fluorescence from these excited levels. These results improve upon and extend those of Reinhold et al. [J. Chem. Phys. 112, 10754 (2000)]. Several decay pathways are open to these levels including fluorescence, predissociation, and autoionization. We present theoretical results for each of these processes, each calculated using the simplest but still appropriate level of theory. In particular, the theoretical calculations provide a quantitative explanation of the dramatic vibrational dependence of the observed lifetimes, the isotope dependence of the lifetimes for levels well localized within the H potential well and therefore not subject to significant tunneling, and an insight into the role of enhanced tunneling in autoionization. In these calculations each of the rovibrational levels of the H state is treated individually, without having to engage in a global coupled-state calculation.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.002
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
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 head0.005
GPT teacher head0.231
Teacher spread0.226 · 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 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

Citations16
Published2006
Admission routes1
Has abstractyes

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