{"id":"W4230773112","doi":"10.1139/tcsme-2017-0031","title":"DEVELOPMENT OF AN ARTICULATION ROBOT ARM","year":2017,"lang":"en","type":"article","venue":"Transactions of the Canadian Society for Mechanical Engineering","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Articulation (sociology); Robot; Robotic arm; Computer science; Engineering; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004185283,0.0004949131,0.0004619329,0.0005217683,0.0004368569,0.0005709341,0.001161525,0.0009046053,0.005865714],"category_scores_gemma":[0.0004817069,0.0003624505,0.0004525112,0.0002622458,0.0003248156,0.0004214979,0.001117154,0.0006163018,0.003012991],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002526445,"about_ca_system_score_gemma":0.00101904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008215228,"about_ca_topic_score_gemma":0.0006610951,"domain_scores_codex":[0.9996278,0.00002795039,0.00001988819,0.00007479572,0.000200271,0.00004915178],"domain_scores_gemma":[0.9997224,0.00003383641,0.00003443494,0.00004902852,0.0001169086,0.00004339633],"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":[0.0003046533,0.000153216,0.001979021,0.00043597,0.00005051521,0.000530118,0.0002266138,0.04737262,0.4498271,0.01897326,0.003285779,0.4768611],"study_design_scores_gemma":[0.0001732062,0.00264795,0.005091043,0.0001637798,0.0001413149,0.002170533,0.000143506,0.5382062,0.2901139,0.00443211,0.1565825,0.0001339395],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04378108,0.000431111,0.9326587,0.0001802593,0.0002364802,0.0001887462,0.00007150737,0.002692183,0.01975989],"genre_scores_gemma":[0.4435025,0.0003875887,0.5323622,0.0001082486,0.00005082422,0.0002093563,0.0002533066,0.0001583613,0.02296768],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005865714,"threshold_uncertainty_score":0.0196228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01808047752398885,"score_gpt":0.222598107294413,"score_spread":0.2045176297704242,"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."}}