{"id":"W2417740159","doi":"","title":"Rendering of virtual fixtures for MIS using generalized sigmoid functions.","year":2006,"lang":"en","type":"article","venue":"PubMed","topic":"Teleoperation and Haptic Systems","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Robarts Clinical Trials","funders":"","keywords":"Haptic technology; Sigmoid function; Computer science; Rendering (computer graphics); Potential field; Force field (fiction); Field (mathematics); Class (philosophy); Reflection (computer programming); Function (biology); Simulation; Artificial intelligence; Mathematics; Physics; Artificial neural network","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":[0.0004923398,0.0007644307,0.0003241143,0.0003934746,0.0001542038,0.001056976,0.000543298,0.0008145304,0.004542611],"category_scores_gemma":[0.001841042,0.0003211336,0.0006583027,0.00023161,0.0003779668,0.0008396495,0.0008925399,0.0005834586,0.0005526056],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003434611,"about_ca_system_score_gemma":0.0003085342,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008716842,"about_ca_topic_score_gemma":0.000684683,"domain_scores_codex":[0.9998431,0.00004706638,0.00000929169,0.00001591433,0.00007068095,0.00001384294],"domain_scores_gemma":[0.9996767,0.0001881559,0.00002392145,0.00004861646,0.00003778989,0.00002477584],"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":[0.0004167625,0.00006403353,0.0006301629,0.0003414675,0.00006292779,0.0008029579,0.0005523419,0.699475,0.11711,0.03993335,0.004077881,0.1365331],"study_design_scores_gemma":[0.00002809707,0.00005506041,0.0002244252,0.00002563949,0.000008011346,0.000282031,0.00004252873,0.9746649,0.01401603,0.004893928,0.00573077,0.00002863108],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02648036,0.000215456,0.9691473,0.0001620368,0.0001057019,0.000036821,0.00008337409,0.0007908986,0.002978104],"genre_scores_gemma":[0.7381647,0.0004683702,0.2540823,0.00007659924,0.00002858853,0.00007638863,0.000111957,0.0002708501,0.00672028],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004542611,"threshold_uncertainty_score":0.01519656,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02480851748262936,"score_gpt":0.1952387038353651,"score_spread":0.1704301863527357,"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."}}