{"id":"W4289875256","doi":"","title":"Detecting Legionella pneumophila with Digitally Photocorroding Biosensor","year":2017,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Legionella and Acanthamoeba research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut interdisciplinaire d'innovation technologique; Université de Sherbrooke","funders":"","keywords":"Legionella pneumophila; Biosensor; Legionella; Computer science; Microbiology; Materials science; Bacteria; Biology; Nanotechnology","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":[0.0004369273,0.0005345723,0.0003802218,0.0003714014,0.0001895845,0.0007264651,0.0007162307,0.001526714,0.003926306],"category_scores_gemma":[0.0007731244,0.0003147925,0.0003077771,0.0003168435,0.000350398,0.0007021423,0.0005101218,0.0005734939,0.001415139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000568555,"about_ca_system_score_gemma":0.0001699889,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004189165,"about_ca_topic_score_gemma":0.0005694111,"domain_scores_codex":[0.9994099,0.00006950174,0.00002353649,0.0002184342,0.0002147229,0.00006392246],"domain_scores_gemma":[0.9996277,0.0001766287,0.00004943119,0.00005210712,0.00007094595,0.00002321464],"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":[0.00006572187,0.00002386703,0.000206209,0.00004935022,0.000004886198,0.00003967387,0.00001993182,0.00006640272,0.9943223,0.0001159165,0.0002300967,0.004855751],"study_design_scores_gemma":[0.0000114336,0.0001279376,0.0009286895,0.000005208393,0.00001367732,0.0001230976,0.00002218469,0.002316275,0.9944007,0.000080597,0.001959987,0.00001025959],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8728267,0.003248076,0.1007998,0.001587357,0.000644731,0.0001671958,0.0007208604,0.002526843,0.01747844],"genre_scores_gemma":[0.9180632,0.001417332,0.05784657,0.0007920133,0.000132913,0.0001100834,0.0003451134,0.00009139624,0.0212015],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003926306,"threshold_uncertainty_score":0.01313478,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01806762928508488,"score_gpt":0.2512608260590209,"score_spread":0.233193196773936,"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."}}