{"id":"W2027354549","doi":"10.4161/bioe.28599","title":"A commentary on the role of molecular technology and automation in clinical diagnostics","year":2014,"lang":"en","type":"article","venue":"Bioengineered","topic":"Bacterial Identification and Susceptibility Testing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Infection and Immunity","funders":"","keywords":"Clinical microbiology; Microbiology; Molecular diagnostics; Identification (biology); Polymerase chain reaction; Yeast; Biology; Computational biology; Medicine; Bioinformatics; Genetics","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":[0.000284266,0.00004913486,0.00007144637,0.00004762075,0.0000130033,0.000005814332,0.00007551307,0.00008571719,0.000002639528],"category_scores_gemma":[0.0008150234,0.00004014471,0.00001988513,0.00008137006,0.00005707672,9.452468e-7,0.0000369058,0.0000522895,0.000001331374],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000003018774,"about_ca_system_score_gemma":0.00000541363,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006674328,"about_ca_topic_score_gemma":0.000007335893,"domain_scores_codex":[0.9995387,0.00006286843,0.0001850621,0.0001172328,0.00003392188,0.00006221837],"domain_scores_gemma":[0.9996488,0.00006357412,0.00004152751,0.0002057628,0.00002391962,0.00001640051],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0000159933,0.000091853,0.04699176,0.000009102397,0.00001297076,2.473095e-7,0.0000195973,0.00001684618,0.9342284,0.004952747,0.00077913,0.01288142],"study_design_scores_gemma":[0.001099823,0.0007273773,0.2378338,0.00006803782,0.00002179716,0.000003903453,0.0002124576,0.01089561,0.7149553,0.002981333,0.0309303,0.000270272],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970975,0.0001630804,0.0003563568,0.002146775,0.00004961271,0.0001006963,0.000004164636,0.00001024721,0.00007157533],"genre_scores_gemma":[0.9991105,0.00005595986,0.0003522366,0.0004050972,0.00003373401,0.000007988036,0.00002586645,0.000004994835,0.000003644518],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.219273,"threshold_uncertainty_score":0.1637054,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00829370322423413,"score_gpt":0.2520521100034825,"score_spread":0.2437584067792484,"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."}}