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Femtosecond laser pulse filamentation characterized by polymer gel dosimetry and Fricke dosimetry

2010· article· en· W1995955602 on OpenAlexaff
Ridthee Meesat, Jean‐François Allard, D. Houde, Luc Tremblay, Abdelouahed Khalil, Jean‐Paul Jay‐Gerin, Martin Lepage

Bibliographic record

VenueJournal of Physics Conference Series · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Matter Interactions and Applications
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsFilamentationFemtosecondLaserDosimetryIonizationDosimeterMaterials scienceOpticsElectronAtomic physicsRadiationPhysicsNuclear physicsIon

Abstract

fetched live from OpenAlex

A femtosecond laser pulse that can generate water radiolysis species was studied in view of its potential medical and biological applications. Intense ultra-short laser pulses can propagate in liquid water, leading to self-focusing and filamentation. Briefly, electrons produced by either multiphoton or tunnel ionization are further accelerated by the electric field of the pulse in an inverse Bremsstrahlung effect. If the electrons acquire enough kinetic energy, they will give rise to a second generation of electrons by impact ionization of other molecules in an avalanche-like process. The geometry and trajectory of femtosecond filaments were captured within a polymer gel dosimeter and imaged by magnetic resonance imaging (MRI) at high resolution. The results revealed that changing pulse duration modifies the penetration of the filament track in the medium. In addition, we used Fricke dosimetry to measure the absorbed dose and dose rate of the femtosecond laser pulse filamentation. A very high dose rate of 5.3 × 1012 Gy/s was calculated in filaments having a diameter of ∼600 μm.

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 categoriesInsufficient payload (model declined to judge)
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 score0.090
Threshold uncertainty score0.999

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.008
GPT teacher head0.248
Teacher spread0.240 · 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.

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

Citations7
Published2010
Admission routes1
Has abstractyes

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