{"id":"W4206863589","doi":"","title":"High resolution Surface Plasmon Resonance Imaging (SPRI) for the early detection and study of bacteria","year":2018,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Advanced Biosensing Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Magnetic resonance imaging; Surface plasmon resonance; Surface plasmon; Resolution (logic); Plasmon; Optoelectronics; Materials science; Nanotechnology; Computer science; Nanoparticle; Medicine; Radiology","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":[0.001591183,0.001137564,0.001228848,0.001000662,0.0005449306,0.001424518,0.0009003471,0.002067456,0.007677861],"category_scores_gemma":[0.001405792,0.0006331194,0.0007401578,0.0007143922,0.0008802807,0.001402837,0.001127759,0.002317393,0.004856302],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005469324,"about_ca_system_score_gemma":0.0003943167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000327138,"about_ca_topic_score_gemma":0.0003345397,"domain_scores_codex":[0.9987389,0.0002278498,0.00003151489,0.0003223003,0.0005524479,0.0001268919],"domain_scores_gemma":[0.9993268,0.0003008754,0.00007333758,0.00007660686,0.0001487259,0.00007368059],"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":[0.00006350499,0.0000466024,0.0001501489,0.000364384,0.00001160794,0.00005337226,0.00004931154,0.0003116466,0.9720448,0.001554469,0.001306548,0.02404358],"study_design_scores_gemma":[0.00001883394,0.0002772229,0.001015138,0.00003557086,0.00003225599,0.0005347007,0.00009790139,0.01139337,0.9679831,0.001926316,0.01664924,0.00003641617],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1919177,0.05158746,0.6932902,0.007910014,0.002071693,0.0004426421,0.001265245,0.006406729,0.0451083],"genre_scores_gemma":[0.603542,0.02940678,0.3231877,0.002091659,0.001093904,0.0002607991,0.001050084,0.0007117781,0.03865536],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007677861,"threshold_uncertainty_score":0.02568495,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01084394010348725,"score_gpt":0.2469494757735525,"score_spread":0.2361055356700653,"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."}}