{"id":"W3173419570","doi":"10.30699/mmlj17.4.1.1","title":"Lean six sigma process improvement in specimen receiving to improve stat chemistry turnaround times","year":2021,"lang":"en","type":"article","venue":"Modern Medical Laboratory Journal","topic":"Clinical Laboratory Practices and Quality Control","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Lean Six Sigma; Turnaround time; Six Sigma; Quality management; Quality assurance; Workflow; Operations management; Lean manufacturing; Process (computing); Process management; Computer science; Engineering; Manufacturing engineering; External quality assessment; Management system; Database","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":[0.01448386,0.0008886161,0.0006618015,0.002169621,0.001502892,0.004057433,0.001427747,0.0007037796,0.001557648],"category_scores_gemma":[0.01310544,0.0004269398,0.0007929783,0.003215136,0.001296169,0.001399344,0.002153889,0.001242148,0.0006609291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003087444,"about_ca_system_score_gemma":0.01154636,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004041619,"about_ca_topic_score_gemma":0.005837857,"domain_scores_codex":[0.9880221,0.004669589,0.001073805,0.0008875401,0.004602992,0.0007439252],"domain_scores_gemma":[0.9828069,0.004898348,0.003554475,0.001806866,0.006173977,0.0007593539],"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":[0.001096266,0.002423065,0.06343831,0.001812915,0.0001763222,0.0008963341,0.007320949,0.07469383,0.05580731,0.01110473,0.007231339,0.7739986],"study_design_scores_gemma":[0.0008427204,0.0176111,0.1392909,0.002944473,0.0005257217,0.002219588,0.01940178,0.3220167,0.2903054,0.06060693,0.1435084,0.0007261646],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.509728,0.001490901,0.4650134,0.004183451,0.0002108764,0.002338014,0.0005297165,0.003660269,0.01284537],"genre_scores_gemma":[0.6340211,0.0007040264,0.3609114,0.0006771997,0.00006213566,0.0006063036,0.0005045471,0.0001346307,0.00237853],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01448386,"threshold_uncertainty_score":0.07659894,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01807630303570529,"score_gpt":0.344615539857605,"score_spread":0.3265392368218997,"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."}}