MétaCan
Menu
Back to cohort
Record W2065919434 · doi:10.1063/1.1615754

Low-energy electron-energy-loss spectroscopy of electronic transitions in solid carbon dioxide

2003· article· en· W2065919434 on OpenAlexaff
Mathieu C. Deschamps, M. Michaud, Léon Sanche

Bibliographic record

VenueThe Journal of Chemical Physics · 2003
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Chemical Physics Studies
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsRydberg formulaAtomic physicsElectron energy loss spectroscopyValence electronElectronValence (chemistry)ChemistrySpectroscopyPhase transitionSpectral lineCondensed matter physicsPhysicsIonization

Abstract

fetched live from OpenAlex

We report electron-energy-loss spectra of solid films of CO2 for electronic transitions induced by 15, 19.4, and 25 eV incident electrons. All spectra were obtained under sufficiently small electron exposures so as to avoid sample damages. The use of a low-energy electron along with the backscattering geometry give access to spin- and symmetry-forbidden transitions while the effect of the condensed phase makes it possible to modify the energy, ordering, and magnitude of most gas-phase transitions. The most noticeable observation is the disappearance of all sharp energy-loss peaks attributed to a Rydberg series of CO2 in the gas phase. In contrast, transitions to the molecular valence Δu3,1 and Σu−3,1 states are located virtually at the same energy as in the gas phase. The strong dipole-allowed valence Σu+1 transition is found shifted to lower energy by about 0.3 eV while transitions to mixed Rydberg-valence Πg3,1 and Πu1 states are both shifted to higher energy by about 0.4–0.5 eV. The lowest valence Σu+3 transition is ascribed to the lowest energy-loss feature in the solid at 7.9 eV.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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)0.0010.000

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 head0.004
GPT teacher head0.232
Teacher spread0.228 · 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

Citations14
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of Chemical PhysicsSame topicAdvanced Chemical Physics StudiesFrench-language works237,207