MétaCan
Menu
Back to cohort
Record W2051071943 · doi:10.1364/boe.5.000016

Towards a bimodal proximity sensor for in situ neurovascular bundle detection during dental implant surgery

2013· article· en· W2051071943 on OpenAlexaff
Jessie R. Weber, François Baribeau, P. Grenier, Frédéric Émond, S. Dubois, François Duchesne, Marc Girard, Timothy D. Pope, Pascal Gallant, Ozzy Mermut, Hassan Moghadam

Bibliographic record

VenueBiomedical Optics Express · 2013
Typearticle
Languageen
FieldDentistry
TopicDental Radiography and Imaging
Canadian institutionsOttawa HospitalInstitut National d'Optique
Fundersnot available
KeywordsNeurovascular bundleOptical coherence tomographyBundleMaterials scienceBiomedical engineeringRangingImaging phantomMedicineAnatomyRadiologyComputer science

Abstract

fetched live from OpenAlex

Proof of concept results are presented towards an in situ bimodal proximity sensor for neurovascular bundle detection during dental implant surgery using combined near infrared absorption (NIR) and optical coherence tomography (OCT) techniques. These modalities are shown to have different sensitivity to the proximity of optical contrast from neurovascular bundles. NIR AC and DC signals from the pulsing of an artery enable qualitative ranging of the bundle in the millimeter range, with best sensitivity around 0.5-3mm distance in a custom phantom setup. OCT provides structural mapping of the neurovascular bundle at sub-millimeter distances in an ex vivo human jaw bone. Combining the two techniques suggests a novel ranging system for the surgeon that could be implemented in a "smart drill." The proximity to the neurovascular bundle can be tracked in real time in the range of a few millimeters with NIR signals, after which higher resolution imaging OCT to provide finer ranging in the sub-millimeter distances.

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 score0.486
Threshold uncertainty score0.848

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 head0.013
GPT teacher head0.243
Teacher spread0.229 · 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

Citations13
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueBiomedical Optics ExpressSame topicDental Radiography and ImagingFrench-language works237,207