{"id":"W4312679461","doi":"10.1109/biorob52689.2022.9925302","title":"Simulating and Optimizing Nasopharyngeal Swab Insertion Paths for use in Robotics","year":2022,"lang":"en","type":"article","venue":"2022 9th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob)","topic":"SARS-CoV-2 detection and testing","field":"Medicine","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Robotics; Artificial intelligence; Leverage (statistics); Computer science; Robot; Nasal cavity; Medical robotics; Simulation; Medicine; Surgery","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005676489,0.0008966282,0.0004584206,0.000452859,0.0004011887,0.0007390952,0.0006609465,0.001170475,0.002401529],"category_scores_gemma":[0.002543352,0.0004909989,0.0006294991,0.0002320158,0.0006947797,0.000405287,0.0007426816,0.0004576297,0.0003259109],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005636721,"about_ca_system_score_gemma":0.00165827,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006777578,"about_ca_topic_score_gemma":0.005706364,"domain_scores_codex":[0.9997614,0.00008208736,0.00001394577,0.00002972207,0.00007150193,0.00004129458],"domain_scores_gemma":[0.9992525,0.0004800062,0.00008199785,0.00004567142,0.00008692955,0.00005291746],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003313002,0.00001914493,0.0004177151,0.00001791126,0.000003966121,0.00003904835,0.00001982688,0.9957703,0.001096933,0.0003415186,0.00006984969,0.002170599],"study_design_scores_gemma":[0.00001040523,0.00004833374,0.0001271052,0.000004817325,0.000003357964,0.00001482064,0.00002697829,0.9981993,0.0008570122,0.0004258562,0.0002772704,0.000004647919],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3735276,0.0004254168,0.6124154,0.00056993,0.0001096745,0.0003340902,0.0004278964,0.001189795,0.01100027],"genre_scores_gemma":[0.8956835,0.0002718837,0.1007904,0.0000596499,0.000009242833,0.0002897426,0.0002574389,0.0001187256,0.002519363],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006777578,"threshold_uncertainty_score":0.01347625,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07465963783262095,"score_gpt":0.3242484158239624,"score_spread":0.2495887779913415,"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."}}