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Record W4213440103 · doi:10.1093/mnras/stac501

Dissociative recombination and rotational transitions of D+2 in collisions with slow electrons

2022· article· en· W4213440103 on OpenAlexfundno aff
M. D. Epée Epée, Ousmanou Motapon, Nicolina Pop, F. Iacob, E. Roueff, I. F. Schneider, J. Zs. Mezei

Bibliographic record

VenueMonthly Notices of the Royal Astronomical Society · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAtomic and Molecular Physics
Canadian institutionsnot available
FundersNemzeti Kutatási, Fejlesztési és Innovaciós AlapCommissariat à l'Énergie Atomique et aux Énergies AlternativesCentre National de la Recherche ScientifiqueRégion NormandieFederación Española de Enfermedades RarasAgence Nationale de la RechercheCentre National d’Etudes SpatialesCommunauté Université Grenoble AlpesLabex EMC3Agence Universitaire de la FrancophonieEuropean Commission
KeywordsDissociative recombinationPhysicsAtomic physicsRecombinationElectronIonElectron captureDissociation (chemistry)Nuclear physics

Abstract

fetched live from OpenAlex

ABSTRACT Rate coefficients for dissociative recombination and state-to-state rotational transitions of the D$_{2}^{+}$ ion induced by collisions with very low-energy electrons have been reported following our previous studies on HD+ and H$_{2}^{+}$. The same molecular structure data sets, excitations ($N_{i}^{+} \rightarrow$$N_{f}^{+}=N_{i}^{+}+2$ for $N_{i}^{+}=0$ to 10) and de-excitations ($N_{i}^{+}\rightarrow N_{f}^{+}=N_{i}^{+}-2$, for $N_{i}^{+}=2$ to 10) were used for collision energies ranging from 0.01 meV to 0.3 eV. Isotopic effects for dissociative recombination and rotational transitions of the vibrationally relaxed targets are presented.

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 score0.467
Threshold uncertainty score0.250

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 head0.004
GPT teacher head0.195
Teacher spread0.192 · 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

Citations9
Published2022
Admission routes1
Has abstractyes

Explore more

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