{"id":"W4282926429","doi":"10.1177/17298806221104906","title":"A review on structural development and recognition–localization methods for end-effector of fruit–vegetable picking robots","year":2022,"lang":"en","type":"review","venue":"International Journal of Advanced Robotic Systems","topic":"Soft Robotics and Applications","field":"Engineering","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Artificial intelligence; Robot; Feature (linguistics); Adaptability; Monocular; Automation; Computer vision; Machine vision; Robot end effector; Field (mathematics); 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":[0.0005389923,0.001253328,0.001009577,0.001780885,0.000355026,0.001034401,0.001108143,0.001263817,0.004292869],"category_scores_gemma":[0.0006980008,0.0007630134,0.00106465,0.001730386,0.0004818568,0.002061985,0.0006234792,0.001009601,0.002860136],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004476432,"about_ca_system_score_gemma":0.0008277683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008808387,"about_ca_topic_score_gemma":0.0008100704,"domain_scores_codex":[0.9995236,0.0000414955,0.00007136953,0.0001387832,0.0001933809,0.00003129209],"domain_scores_gemma":[0.9995661,0.0001750027,0.000072482,0.00003117677,0.0001337235,0.0000215178],"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":[0.00009616691,0.00008937313,0.000470889,0.02030809,0.0001129285,0.000282729,0.0001873667,0.005814321,0.03098031,0.01082829,0.01830006,0.9125295],"study_design_scores_gemma":[0.00001106381,0.0004198226,0.001633451,0.002302799,0.0001989407,0.001743477,0.0001268287,0.01167362,0.01661227,0.004938303,0.9602164,0.0001230303],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.003143299,0.8656291,0.1156546,0.0005014543,0.001240572,0.00006718317,0.0001455692,0.0004743036,0.01314398],"genre_scores_gemma":[0.02524163,0.8786977,0.07855899,0.0006710708,0.0009531202,0.0001447247,0.0005537488,0.0001388152,0.01504015],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004292869,"threshold_uncertainty_score":0.01436108,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07509784031552354,"score_gpt":0.3888798761617235,"score_spread":0.3137820358462,"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."}}