{"id":"W2164834344","doi":"10.1109/robot.1996.509246","title":"Curvature based shape estimation using tactile sensing","year":2002,"lang":"en","type":"article","venue":"","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Curvature; Tactile sensor; Surface (topology); Computer vision; Computer science; Spline (mechanical); Point (geometry); Artificial intelligence; Mathematics; Geometry; Engineering; Robot; Mechanical engineering","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":[0.0003785598,0.0005742588,0.0007568926,0.001240664,0.0002293835,0.0006277831,0.0007831622,0.0008882902,0.0008258609],"category_scores_gemma":[0.001576562,0.0003866581,0.0006507697,0.0006629407,0.000667118,0.001524247,0.0007055074,0.0003871595,0.0004356125],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000350129,"about_ca_system_score_gemma":0.0002854856,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001140295,"about_ca_topic_score_gemma":0.001437369,"domain_scores_codex":[0.9995889,0.00006597395,0.00001974615,0.0001032494,0.0001951218,0.00002699882],"domain_scores_gemma":[0.9990692,0.0003052618,0.000144033,0.0002410287,0.0001951409,0.00004546949],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002407344,0.0001226319,0.003592213,0.0002090438,0.0001388615,0.0002783207,0.0002876423,0.1643595,0.2312696,0.01412027,0.001461522,0.5839196],"study_design_scores_gemma":[0.00001131991,0.0001283063,0.001971069,0.000008097484,0.00001718007,0.0002868797,0.00002338372,0.9519172,0.03841693,0.005207325,0.00193595,0.00007639026],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02285067,0.0001579527,0.9756939,0.0000679185,0.00001923304,0.00001441978,0.00002419516,0.0005096403,0.0006620558],"genre_scores_gemma":[0.5263442,0.0003255391,0.46946,0.0001236948,0.00006670023,0.00004753808,0.0001393186,0.0001315708,0.003361404],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001240664,"threshold_uncertainty_score":0.002762735,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.042363578274415,"score_gpt":0.2323213423101463,"score_spread":0.1899577640357313,"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."}}