{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002757336,0.00009983405,0.0002111318,0.00003957294,0.00002175241,0.000009975132,0.0001948993,0.0001578715,0.0001099165],"category_scores_gemma":[0.0005527176,0.0001022194,0.00002371731,0.000598195,0.0000863638,0.00006727659,0.00001576506,0.0002532462,0.00003937096],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006368548,"about_ca_system_score_gemma":0.00007641334,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":5.277074e-7,"about_ca_topic_score_gemma":9.002449e-7,"domain_scores_codex":[0.9989917,0.00001134679,0.0005909184,0.0001802336,0.00009747384,0.0001283678],"domain_scores_gemma":[0.9993924,0.0001767299,0.00004669113,0.0002570204,0.00007129106,0.00005586771],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003512975,0.001027468,0.1724274,0.01236694,0.0002911734,0.00002658944,0.0007030472,0.6455953,0.02450583,0.006646574,0.08459171,0.05178288],"study_design_scores_gemma":[0.001837972,0.00001101002,0.05984804,0.0007503812,0.00005412105,0.000002018634,0.0002130039,0.9058987,0.01879833,0.008001725,0.004158905,0.0004257471],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7369856,0.001803948,0.09039214,0.007473719,0.0009655621,0.0007182197,0.000008638362,0.003633621,0.1580186],"genre_scores_gemma":[0.9987374,0.00004041336,0.0005025885,0.0001961389,0.00008161485,0.00008650647,0.00001845471,0.00001244787,0.0003244143],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2617518,"threshold_uncertainty_score":0.4168388,"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."}}