{"id":"W2282118241","doi":"10.1149/ma2014-01/40/1482","title":"An Ultra Low Noise Optoelectronic Module Enables an in Situ Range-Finder Probe to Locate a Neurovascular Bundle in Dental Implant Surgery","year":2014,"lang":"en","type":"article","venue":"ECS Meeting Abstracts","topic":"Laser Applications in Dentistry and Medicine","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ottawa Hospital; Institut National d'Optique","funders":"","keywords":"Neurovascular bundle; Optical coherence tomography; Dental implant; Implant; Medicine; Cone beam computed tomography; Medical imaging; Temporomandibular joint; Magnetic resonance imaging; Biomedical engineering; Materials science; Surgery; Radiology; Dentistry; Computed tomography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003812134,0.0004775417,0.0002634485,0.000383764,0.0002066799,0.0004986333,0.0009276721,0.001121456,0.002215326],"category_scores_gemma":[0.0005019916,0.0003763658,0.0002934274,0.0002601262,0.0003487171,0.0008067061,0.0005966975,0.0004178504,0.0007434645],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003790767,"about_ca_system_score_gemma":0.0003214804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002773357,"about_ca_topic_score_gemma":0.0006014079,"domain_scores_codex":[0.9994676,0.00007668197,0.0000316618,0.0001349963,0.0002410565,0.00004804624],"domain_scores_gemma":[0.9996932,0.00008621196,0.00009582638,0.0000379936,0.00006452534,0.0000223731],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001413908,0.000101337,0.00153585,0.0001911872,0.00001422889,0.0002476875,0.0001005161,0.0005428158,0.95456,0.0009448326,0.0008075626,0.04081264],"study_design_scores_gemma":[0.0000689102,0.002477872,0.01588602,0.0001091529,0.0001290074,0.004566046,0.0002014121,0.03921311,0.9016278,0.0008334904,0.03473035,0.0001568759],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.427009,0.005155887,0.552655,0.00127603,0.0007022576,0.0003905259,0.0004388691,0.002073516,0.01029893],"genre_scores_gemma":[0.8111676,0.001162013,0.1769248,0.0007605791,0.0001647868,0.0002569084,0.0001627966,0.00007589694,0.009324676],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002215326,"threshold_uncertainty_score":0.007411003,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01409392328120278,"score_gpt":0.2618169893637207,"score_spread":0.2477230660825179,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}