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Record W2151907147 · doi:10.3109/09553002.2011.577505

Measurement of inelastic cross sections for low-energy electron scattering from DNA bases

2011· article· en· W2151907147 on OpenAlexafffund
M. Michaud, M. Bazin, Le ́on Sanche

Bibliographic record

VenueInternational Journal of Radiation Biology · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAtomic and Molecular Physics
Canadian institutionsMAB-Mackay Rehabilitation CentreUniversité de Sherbrooke
FundersCanadian Institutes of Health Research
KeywordsThymineAtomic physicsChemistryIonizationElectronNucleobaseElectron ionizationSpectral lineMoleculeExcitationSubstrate (aquarium)Ionizing radiationArgonDNAMolecular physicsIrradiationPhysics

Abstract

fetched live from OpenAlex

PURPOSE: To determine experimentally the absolute cross sections (CS) to deposit various amount of energies into DNA bases by low-energy electron (LEE) impact. MATERIALS AND METHODS: Electron energy loss (EEL) spectra of DNA bases were recorded for different LEE impact energies on the molecules deposited at very low coverage on an inert argon (Ar) substrate. Following their normalisation to the effective incident electron current and molecular surface number density, the EEL spectra were then fitted with multiple Gaussian functions in order to delimit the various excitation energy regions. The CS to excite a molecule into its various excitation modes were finally obtained from computing the area under the corresponding Gaussians. RESULTS: The EEL spectra and absolute CS for the electronic excitations of pyrimidine and the DNA bases thymine, adenine, and cytosine by electron impacts below 18 eV were reported for the molecules deposited at about monolayer coverage on a solid Ar substrate. CONCLUSIONS: The CS for electronic excitations of DNA bases by LEE impact were found to lie within the 10(216) to 10(218) cm(2) range. The large value of the total ionisation CS indicated that ionisation of DNA bases by LEE is an important dissipative process via which ionising radiation degrades and is absorbed in DNA.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.472
Threshold uncertainty score0.240

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 head0.018
GPT teacher head0.271
Teacher spread0.254 · 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 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

Citations30
Published2011
Admission routes2
Has abstractyes

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