{"id":"W2736763384","doi":"10.20286/jeas.v3i2.19","title":"Safety Assessment for Industrial Robots","year":2016,"lang":"en","type":"article","venue":"Nova Journal of Engineering and Applied Sciences","topic":"Occupational Health and Safety Research","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Robot; Reliability (semiconductor); Markov chain; Risk analysis (engineering); Work (physics); Computer science; Engineering; Reliability engineering; Business; 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":[0.001162631,0.0005803826,0.0003729595,0.002061744,0.0004082472,0.0004952104,0.0005146416,0.0005473729,0.002316509],"category_scores_gemma":[0.006566296,0.0001635264,0.0007823689,0.0005798949,0.000323116,0.0008266041,0.0005411596,0.0003320926,0.0002799658],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009134337,"about_ca_system_score_gemma":0.0007916496,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003793288,"about_ca_topic_score_gemma":0.001879546,"domain_scores_codex":[0.9991043,0.0002358057,0.0000526265,0.00011212,0.0004321564,0.00006296585],"domain_scores_gemma":[0.9973364,0.001410088,0.0004112386,0.0001158491,0.0006625567,0.00006371335],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0002999001,0.0001904575,0.05510221,0.0003685198,0.0001249156,0.0003511344,0.0004483844,0.7958189,0.01126501,0.01168433,0.001687451,0.1226588],"study_design_scores_gemma":[0.00001329319,0.0004288563,0.01877351,0.00004245933,0.00005145307,0.0002871842,0.0002692931,0.9639874,0.002842903,0.01172505,0.001545119,0.00003347387],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4314924,0.0009022396,0.5570002,0.0002759751,0.00005830267,0.0002848148,0.0003711042,0.000466681,0.009148401],"genre_scores_gemma":[0.9827117,0.0002392148,0.01534831,0.00001700757,0.00001700728,0.00006003083,0.0002220532,0.0000148775,0.001369797],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003793288,"threshold_uncertainty_score":0.007749498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1899117306783419,"score_gpt":0.4751173300192219,"score_spread":0.28520559934088,"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."}}