{"id":"W4289782781","doi":"","title":"Quantum Semiconductor Photonic Biosensing Platform for Detection of Legionella Pneumophila in Industrial Water","year":2017,"lang":"fr","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Biosensors and Analytical Detection","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut interdisciplinaire d'innovation technologique; Université de Sherbrooke","funders":"","keywords":"Legionella pneumophila; Photonics; Biosensor; Legionella; Semiconductor; Optoelectronics; Nanotechnology; Materials science; Computer science; Biology; Bacteria","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":[0.0002058384,0.0003971033,0.0003250473,0.0002485427,0.0003067088,0.0006513157,0.0004724854,0.001079071,0.002441407],"category_scores_gemma":[0.0002188117,0.0002668046,0.0002569484,0.0002156984,0.0002903283,0.0005519849,0.0005236104,0.0003933891,0.0008188261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004745955,"about_ca_system_score_gemma":0.000369796,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004695124,"about_ca_topic_score_gemma":0.0008580997,"domain_scores_codex":[0.999779,0.00002369281,0.000005198623,0.00006748075,0.00008837266,0.00003622952],"domain_scores_gemma":[0.9998729,0.00003614922,0.00001901755,0.00001150168,0.00004169187,0.00001865469],"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":[0.00004070385,0.00002593693,0.00008516898,0.00005776947,0.000005399158,0.00004883014,0.00001948587,0.0002290314,0.9960893,0.0003859775,0.0002786613,0.002733757],"study_design_scores_gemma":[0.0000146643,0.0002264515,0.0006673801,0.00000714666,0.00001582151,0.000069857,0.00004241209,0.007932053,0.9870895,0.0002480659,0.003674743,0.00001199504],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.939715,0.00228135,0.04386425,0.0008209422,0.0003036255,0.0001122963,0.0003420291,0.0007340948,0.01182644],"genre_scores_gemma":[0.9652414,0.001028869,0.02339286,0.0004101201,0.00005831837,0.00008696243,0.0002084656,0.00004852251,0.009524467],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002441407,"threshold_uncertainty_score":0.008167326,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0335080069273999,"score_gpt":0.2300049112893643,"score_spread":0.1964969043619644,"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."}}