{"id":"W2141702479","doi":"10.1109/robot.1997.620008","title":"An eye-hand system for automated paper recycling","year":2002,"lang":"en","type":"article","venue":"","topic":"Image and Object Detection Techniques","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Computer vision","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":[],"consensus_categories":[],"category_scores_codex":[0.0001725909,0.00007672275,0.00009146728,0.00007396202,0.0001828543,0.0002601888,0.0003211317,0.00005262924,0.00003301871],"category_scores_gemma":[0.00001176032,0.00006361959,0.00004276335,0.0001705952,0.00001182477,0.000682931,0.00002794891,0.00003944063,0.00004886158],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003196004,"about_ca_system_score_gemma":0.000005589109,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002555381,"about_ca_topic_score_gemma":0.000004535965,"domain_scores_codex":[0.9993359,0.00002871207,0.0001475075,0.0002285611,0.00008947116,0.0001697867],"domain_scores_gemma":[0.9994493,0.0000272921,0.00003623101,0.0003654583,0.00007233115,0.00004943803],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001408907,0.000229625,0.00007762807,0.0001975809,0.00004470053,0.00003821833,0.001774519,0.00006568148,0.2653692,0.01547014,0.03862643,0.6780922],"study_design_scores_gemma":[0.0001375744,0.0001221232,0.00004941582,0.00001392749,0.000002362013,0.00001134843,0.00003082912,0.4992003,0.4944384,0.0001225011,0.005760041,0.0001111781],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001984843,0.00003786212,0.9827901,0.000155591,0.0002269569,0.0001997778,6.681573e-7,0.005753562,0.008850613],"genre_scores_gemma":[0.8704535,0.000003291617,0.128105,0.0003198404,0.00006272155,0.0000437443,5.19373e-7,0.000007906457,0.001003439],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8684687,"threshold_uncertainty_score":0.2594332,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01517337414084768,"score_gpt":0.2648026049347744,"score_spread":0.2496292307939267,"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."}}