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Record W2132839236 · doi:10.1126/science.1157980

Laser-Induced Electron Tunneling and Diffraction

2008· article· en· W2132839236 on OpenAlexaff
M. Meckel, D. Comtois, D. Zeidler, A. Staudte, D. Pavičić, H. Bandulet, H. Pépin, J. C. Kieffer, R. Dörner, D. M. Villeneuve, P. B. Corkum

Bibliographic record

VenueScience · 2008
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Matter Interactions and Applications
Canadian institutionsNational Research Council CanadaInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsElectronPhotoelectric effectElectron diffractionLaserAtomic physicsDiffractionQuantum tunnellingMolecular orbitalMoleculeIonGas electron diffractionPhysicsMolecular physicsChemistryReflection high-energy electron diffractionOpticsCondensed matter physicsNuclear physicsQuantum mechanics

Abstract

fetched live from OpenAlex

Molecular structure is usually determined by measuring the diffraction pattern the molecule impresses on x-rays or electrons. We used a laser field to extract electrons from the molecule itself, accelerate them, and in some cases force them to recollide with and diffract from the parent ion, all within a fraction of a laser period. Here, we show that the momentum distribution of the extracted electron carries the fingerprint of the highest occupied molecular orbital, whereas the elastically scattered electrons reveal the position of the nuclear components of the molecule. Thus, in one comprehensive technology, the photoelectrons give detailed information about the electronic orbital and the position of the nuclei.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.016
GPT teacher head0.278
Teacher spread0.262 · 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

Citations779
Published2008
Admission routes1
Has abstractyes

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