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Record W2123563817 · doi:10.1088/0031-9155/45/5/317

The effects of dynamic optical properties during interstitial laser photocoagulation

2000· article· en· W2123563817 on OpenAlexaff
Megumi Iizuka, I. Alex Vitkin, Michael C. Kolios, Michael D. Sherar

Bibliographic record

VenuePhysics in Medicine and Biology · 2000
Typearticle
Languageen
FieldEngineering
TopicPhotoacoustic and Ultrasonic Imaging
Canadian institutionsToronto Metropolitan UniversityUniversity of TorontoOntario Institute for Cancer Research
FundersNational Cancer Institute
KeywordsArrhenius equationMaterials scienceLaserNonlinear systemThermalOpticsKineticsThermodynamicsPhysicsClassical mechanics

Abstract

fetched live from OpenAlex

A nonlinear mathematical model was developed and experimentally validated to investigate the effects of changes in optical properties during interstitial laser photocoagulation (ILP). The effects of dynamic optical properties were calculated using the Arrhenius damage model, resulting in a nonlinear optothermal response. This response was experimentally validated by measuring the temperature rise in albumen and polyacrylamide phantoms. A theoretical study of ILP in liver was conducted constraining the peak temperatures below the vaporization threshold. The temperature predictions varied considerably between the static and dynamic scenarios, and were confirmed experimentally in phantoms. This suggests that the Arrhenius model can be used to predict dynamic changes in optical and thermal fields. An increase in temperature rise due to a decrease in light penetration within the coagulated region during ILP of the liver was also demonstrated. The kinetics of ILP are complex and nonlinear due to coagulation, which changes the tissue properties during treatment. These complex effects can be adequately modelled using an Arrhenius damage formulation.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.617
Threshold uncertainty score0.139

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 head0.031
GPT teacher head0.283
Teacher spread0.252 · 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

Citations68
Published2000
Admission routes1
Has abstractyes

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