{"id":"W2727569568","doi":"10.3390/safety3030017","title":"Implications of Articulating Machinery on Operator Line of Sight and Efficacy of Camera Based Proximity Detection Systems","year":2017,"lang":"en","type":"article","venue":"Safety","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Laurentian University","funders":"","keywords":"Sight; Operator (biology); Line (geometry); Artificial intelligence; Computer science; Computer vision; Articulation (sociology); Engineering; Simulation; Engineering drawing","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":[0.009881922,0.0004149307,0.000267652,0.0006509306,0.0006403191,0.002133225,0.0006893609,0.001159767,0.006286446],"category_scores_gemma":[0.1143535,0.0003214212,0.0003431089,0.0002382081,0.00159037,0.00209164,0.001486824,0.0008154674,0.001043984],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008519446,"about_ca_system_score_gemma":0.0009968603,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002064469,"about_ca_topic_score_gemma":0.001603515,"domain_scores_codex":[0.9882322,0.006989854,0.0006609355,0.0008378019,0.00269381,0.0005854648],"domain_scores_gemma":[0.8478333,0.1163575,0.01362715,0.005322034,0.01400561,0.002854431],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.009996373,0.005804768,0.5054082,0.001033602,0.0003756084,0.0007102917,0.01387391,0.0278084,0.1076204,0.005757537,0.002505769,0.3191052],"study_design_scores_gemma":[0.0003967721,0.01734265,0.8880488,0.0005510048,0.0003999713,0.0007464659,0.01662122,0.03433763,0.0305069,0.005091716,0.005687968,0.0002689499],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9764917,0.0002276783,0.009679624,0.0004732953,0.00004690703,0.00009516251,0.00004242262,0.00007918412,0.012864],"genre_scores_gemma":[0.9972887,0.00008155622,0.001933255,0.00009274109,0.00001091693,0.00002159204,0.00001983212,0.00001566487,0.0005358786],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009881922,"threshold_uncertainty_score":0.05226123,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03391389981762872,"score_gpt":0.3606013367526198,"score_spread":0.3266874369349911,"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."}}