{"id":"W4210962827","doi":"10.3390/bios12020105","title":"Selective Detection of Legionella pneumophila Serogroup 1 and 5 with a Digital Photocorrosion Biosensor Using Antimicrobial Peptide-Antibody Sandwich Strategy","year":2022,"lang":"en","type":"article","venue":"Biosensors","topic":"Legionella and Acanthamoeba research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Canada; Institut interdisciplinaire d'innovation technologique; Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Fonds de recherche du Québec – Nature et technologies; Health Canada; CMC Microsystems","keywords":"Legionella pneumophila; Biosensor; Antimicrobial; Microbiology; Legionella; Peptide; Antibody; Chemistry; Chromatography; Medicine; Biology; Biochemistry; Immunology; Bacteria","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001184103,0.0002033933,0.0002043445,0.0001320816,0.0003095871,0.00005297831,0.0001216545,0.00009677568,0.000003041444],"category_scores_gemma":[0.00001949703,0.0001827562,0.00007727787,0.0003178623,0.0001995022,0.00001326796,0.0001888072,0.0001822865,0.000001249743],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003338514,"about_ca_system_score_gemma":0.0001012253,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001578059,"about_ca_topic_score_gemma":0.00002015738,"domain_scores_codex":[0.9986666,0.00008797168,0.0002145513,0.0004714254,0.000246889,0.0003124896],"domain_scores_gemma":[0.999423,0.00001697438,0.0001362119,0.000217253,0.000118925,0.00008758032],"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":[0.0007498902,0.0001231261,0.004923978,0.00003304289,0.00004707589,0.00001564576,0.00006963735,0.0003624442,0.9933398,0.000003786852,0.00007290886,0.0002586288],"study_design_scores_gemma":[0.001053777,0.001453116,0.003367364,0.00001914519,0.00002526952,0.0003974204,0.0004981848,0.0005564676,0.9913229,0.000006900133,0.001008388,0.000291014],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989067,0.00007753403,0.0001036618,0.00003439677,0.00005390824,0.0005230675,0.00008852434,0.00001569788,0.0001965347],"genre_scores_gemma":[0.9993879,0.00005014152,0.00009285563,0.00003468764,0.00009653137,0.00001660521,0.00007244217,0.00003752337,0.0002112933],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002016881,"threshold_uncertainty_score":0.7452582,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01328985671213044,"score_gpt":0.2599594581705668,"score_spread":0.2466696014584364,"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."}}