{"id":"W2498160669","doi":"10.4018/978-1-4666-9522-1.ch023","title":"Design of a Multi-Modal Dexterity Training Interface for Medical and Biological Sciences","year":2015,"lang":"en","type":"book-chapter","venue":"Advances in medical technologies and clinical practice book series","topic":"Teleoperation and Haptic Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Human–computer interaction; Modal; Haptic technology; Interface (matter); Virtual reality; Graphics; Software; Fuzzy logic; User interface; Audio feedback; Training (meteorology); Multimedia; Artificial intelligence; Computer graphics (images); Engineering; Programming language","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","sts","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.003708172,0.0003116533,0.0009171916,0.0001063082,0.00007675334,0.00003658911,0.0004248886,0.001377398,0.00006879317],"category_scores_gemma":[0.01988917,0.0002341269,0.00006617954,0.00004996567,0.003500079,0.0007021986,0.0002509957,0.00102422,0.000002058799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002845588,"about_ca_system_score_gemma":0.0001970526,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002655282,"about_ca_topic_score_gemma":0.00003170445,"domain_scores_codex":[0.9973874,0.00008562129,0.001193701,0.0004924247,0.0005541738,0.000286696],"domain_scores_gemma":[0.9951043,0.004184193,0.0002475083,0.0001956615,0.0001038127,0.0001644897],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003618068,0.00009398614,0.0001078459,0.0004007945,0.0001418394,0.0001061396,0.0002867365,0.0001171981,0.00001104884,0.1062495,0.0003085509,0.8918145],"study_design_scores_gemma":[0.0021702,0.002867889,0.00002659873,0.001847871,0.00008725799,0.0005328169,0.007451883,0.02741854,0.00002483265,0.03492499,0.9218531,0.0007939983],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001364862,0.5930755,0.3235175,0.01139501,0.002691971,0.003063395,0.00007684289,0.002276325,0.06253856],"genre_scores_gemma":[0.07423733,0.7892126,0.1324859,0.0006200464,0.0003009254,0.0001883676,0.0000104514,0.00009389605,0.002850477],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9215446,"threshold_uncertainty_score":0.999919,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1393125067854669,"score_gpt":0.4147767965741685,"score_spread":0.2754642897887016,"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."}}