{"id":"W4288323969","doi":"","title":"Antimicrobial peptide based digital photocorrosion biosensor for detecting Legionella pneumophila","year":2019,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Polydiacetylene-based materials and applications","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Institut interdisciplinaire d'innovation technologique; Université de Sherbrooke","funders":"","keywords":"Legionella pneumophila; Biosensor; Legionella; Antimicrobial; Materials science; Microbiology; Nanotechnology; Chemistry; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001405063,0.0005017525,0.0005246082,0.0001354114,0.0004520641,0.0008556598,0.00108095,0.0004947557,0.00008944391],"category_scores_gemma":[0.0008316457,0.0005570924,0.0004497379,0.0001622933,0.000166881,0.000119936,0.0007984814,0.0005015603,0.00008079676],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000162277,"about_ca_system_score_gemma":0.0003760402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002737311,"about_ca_topic_score_gemma":0.0001000733,"domain_scores_codex":[0.9970453,0.0003641327,0.0006965148,0.001088739,0.0002905174,0.0005147647],"domain_scores_gemma":[0.9940207,0.001561625,0.0007901001,0.002325487,0.001113508,0.0001885622],"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":[0.00004870786,0.0004588236,0.0003570677,0.0008603036,0.0000336934,0.000001378874,0.0003912319,0.0003409614,0.9913487,0.001020613,0.001109988,0.004028565],"study_design_scores_gemma":[0.0008905697,3.387844e-7,0.00006145205,0.00189543,0.00005598981,0.000006251202,0.00003531703,0.01187292,0.9650834,0.0004380278,0.01907087,0.0005894576],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9057366,0.0001385829,0.05972137,0.004001167,0.0003843917,0.001653742,0.002275837,0.0005872792,0.02550104],"genre_scores_gemma":[0.9737983,0.00006587438,0.01726041,0.0001130673,0.0001076599,0.0005066302,0.002043263,0.000125851,0.005978926],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06806174,"threshold_uncertainty_score":0.999688,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01384233428681161,"score_gpt":0.2238889550314583,"score_spread":0.2100466207446467,"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."}}