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Record W2911673211 · doi:10.1002/jbio.201800293

Influence of environmental conditions in bovine bone ablation by ultrafast laser

2019· article· en· W2911673211 on OpenAlexafffund
Fahad Aljekhedab, Wenbin Zhang, H. K. Haugen, Gregory R. Wohl, Munir M. El‐Desouki, Qiyin Fang

Bibliographic record

VenueJournal of Biophotonics · 2019
Typearticle
Languageen
FieldMedicine
TopicLaser Applications in Dentistry and Medicine
Canadian institutionsMcMaster University
FundersOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsCanada Foundation for InnovationOntario Centres of Excellence
KeywordsAblationMaterials scienceLaser ablationLaserFemtosecondComposite materialAnalytical Chemistry (journal)OpticsChemistryEnvironmental chemistry

Abstract

fetched live from OpenAlex

Ultrafast lasers are promising tools for surgical applications requiring precise tissue cutting. Shallow ablation depth and slow rate as well as collateral damage are common barriers limiting the use of laser in clinical applications. Localized cooling with water and/or air jet is known to reduce collateral thermal damage. We studied the influence of environmental conditions including air, compressed air flow, still water and water jet on ablation depth, ablation rate and surface morphology on bovine bone samples with an 800 nm femtosecond laser. At 15 J/cm 2 , no thermal effect was observed by electron microscopy and Raman spectroscopy. The experimental results indicate that environmental conditions play a significant role in laser ablation. The deepest cavity and highest ablation rate were achieved under the compressed air flow condition, which is attributed to debris removal during the ablation process. The shallowest ablation depth and lowest ablation rates were associated with water flushing. For surface morphology, smooth surface and the absence of microcracks were observed under air flow conditions, while rougher surfaces and minor microcracks were observed under other conditions. These results suggest that ultrafast ablation of bone can be more efficient and with better surface qualities if assisted with blowing air jet.

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 score0.474
Threshold uncertainty score0.332

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 head0.004
GPT teacher head0.243
Teacher spread0.239 · 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

Citations20
Published2019
Admission routes2
Has abstractyes

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