{"id":"W4410794210","doi":"10.1093/clinchem/hvaf060","title":"Robotic Process Automation in Laboratory Medicine","year":2025,"lang":"en","type":"article","venue":"Clinical Chemistry","topic":"Robotic Process Automation Applications","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Automation; Process (computing); Medical laboratory; Medicine; Computer science; Engineering; Pathology; Mechanical engineering; Operating system","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":[0.001640755,0.0007594295,0.0006517572,0.001452386,0.0008274099,0.002553547,0.00145035,0.002249412,0.00566218],"category_scores_gemma":[0.002970696,0.0005793246,0.000749694,0.001258731,0.002605163,0.00189748,0.002111829,0.00146236,0.003478122],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001219105,"about_ca_system_score_gemma":0.001255728,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001351275,"about_ca_topic_score_gemma":0.0009595608,"domain_scores_codex":[0.9979462,0.0006056247,0.0001057779,0.0003171696,0.0009200812,0.0001051708],"domain_scores_gemma":[0.9985881,0.0005974444,0.0001744083,0.0002241616,0.0003109541,0.0001049122],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002207925,0.0001484727,0.00161504,0.00220337,0.000073191,0.0005789523,0.0004333474,0.0330957,0.02209803,0.1571402,0.02623194,0.756161],"study_design_scores_gemma":[0.00008911033,0.0008197625,0.003260507,0.001462158,0.0000807519,0.003203667,0.0002998398,0.07018337,0.01970088,0.1714735,0.7291684,0.0002580812],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01275722,0.1689174,0.6725634,0.00815661,0.002910818,0.0002879692,0.0002211431,0.003130948,0.1310545],"genre_scores_gemma":[0.3983481,0.1120751,0.4392069,0.003546324,0.003127154,0.0005449429,0.0004199542,0.0003470209,0.04238463],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00566218,"threshold_uncertainty_score":0.01894188,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01655137850481492,"score_gpt":0.3456299627877125,"score_spread":0.3290785842828975,"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."}}