{"id":"W2801392054","doi":"10.1139/tcsme-2003-0021","title":"OBJECT SHAPE EXPLORATION AND RECOGNITION IN 2D USING A TWO-FINGERED ROBOTIC HAND","year":2004,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Robot Manipulation and Learning","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Object (grammar); Computer vision; Robotic hand; Artificial intelligence; Computer science; Set (abstract data type); Position (finance); Degrees of freedom (physics and chemistry); Cognitive neuroscience of visual object recognition; Tactile sensor; Robot; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0003188648,0.0004525578,0.0005818099,0.0002896898,0.0002794733,0.0005997033,0.0005788984,0.0007772767,0.001231342],"category_scores_gemma":[0.0009498893,0.0004028825,0.0003239312,0.0002750278,0.0006107419,0.001246661,0.0009018492,0.0002771951,0.0003082975],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002381034,"about_ca_system_score_gemma":0.0002533582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001060802,"about_ca_topic_score_gemma":0.001232301,"domain_scores_codex":[0.9996675,0.00006466808,0.00002205916,0.0001032317,0.0001138167,0.00002876994],"domain_scores_gemma":[0.9994815,0.0002654404,0.00005786628,0.0001228764,0.00003259135,0.00003965975],"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":[0.0006819597,0.0001503647,0.001221693,0.0001680093,0.00003846157,0.0005621794,0.0004252323,0.05579827,0.7607858,0.001168776,0.0004343489,0.1785649],"study_design_scores_gemma":[0.0001579026,0.001665559,0.008872424,0.00003724538,0.00003770958,0.002527015,0.0001994466,0.7457994,0.2317527,0.0032848,0.00549492,0.0001708723],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5498366,0.0004297163,0.4450975,0.0001289172,0.00002699166,0.00008363649,0.00009148612,0.001765602,0.002539645],"genre_scores_gemma":[0.7703415,0.0001533697,0.2271561,0.00005665015,0.000007559183,0.00005881315,0.00006671201,0.00003099942,0.002128247],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001231342,"threshold_uncertainty_score":0.004119277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04025146865146736,"score_gpt":0.2275286622189958,"score_spread":0.1872771935675284,"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."}}