{"id":"W4413419635","doi":"10.21872/2024iise_7137","title":"Promoting Safe Use of AMRs by Assessing their Residual Risks and Safety-Related Functions","year":2024,"lang":"en","type":"article","venue":"","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Residual; Risk analysis (engineering); Reliability engineering; Computer science; Business; Engineering; Algorithm","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.01057561,0.001878373,0.0006562677,0.004013475,0.001170556,0.003219686,0.001685231,0.001779546,0.002144986],"category_scores_gemma":[0.02305657,0.0004246607,0.0007238936,0.0007865076,0.001341188,0.004315391,0.00391331,0.001002646,0.001120797],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001476947,"about_ca_system_score_gemma":0.003724703,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003474052,"about_ca_topic_score_gemma":0.003832203,"domain_scores_codex":[0.9848327,0.00433624,0.0007481155,0.0006671598,0.008713898,0.0007019799],"domain_scores_gemma":[0.9746138,0.00603293,0.004937463,0.002318846,0.01130035,0.0007967144],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0006040903,0.0008844698,0.1604556,0.001732295,0.0001729434,0.00100897,0.009234441,0.02881552,0.04367317,0.01798489,0.004375102,0.7310585],"study_design_scores_gemma":[0.0001512164,0.00920585,0.4724991,0.004267248,0.0008156319,0.003985247,0.04025391,0.1461997,0.1159624,0.05208137,0.1536395,0.0009387225],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5255334,0.002887555,0.414653,0.00324344,0.0001731215,0.001645056,0.0002734476,0.002160867,0.04943015],"genre_scores_gemma":[0.8409045,0.001260021,0.1510755,0.0002367282,0.00004647547,0.0004995062,0.0002317613,0.0001731779,0.005572366],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01057561,"threshold_uncertainty_score":0.05592984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1590166651813388,"score_gpt":0.3883201602449798,"score_spread":0.2293034950636409,"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."}}