{"id":"W4206861382","doi":"","title":"Detecting Legionella with digitally photocorroding biosensor","year":2019,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Hermeneutics and Narrative Identity","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut interdisciplinaire d'innovation technologique; Université de Sherbrooke","funders":"","keywords":"Biosensor; Legionella; Computer science; Biology; Materials science; Nanotechnology; 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":[0.0004728668,0.0005363732,0.0003733519,0.0006112523,0.0003586016,0.000791225,0.0007029038,0.001904015,0.003373652],"category_scores_gemma":[0.0008062219,0.0004126441,0.000373806,0.0005014326,0.0005477517,0.0008150813,0.0005826731,0.0009102434,0.001364613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005014393,"about_ca_system_score_gemma":0.0002113059,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004282942,"about_ca_topic_score_gemma":0.001142586,"domain_scores_codex":[0.9992104,0.0001099689,0.00002446242,0.000296689,0.0002714944,0.00008709907],"domain_scores_gemma":[0.9994153,0.000216112,0.0001193247,0.00007083671,0.0001350936,0.00004331611],"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":[0.00007589551,0.00005559204,0.0008335575,0.00011841,0.00001317046,0.0001341233,0.00009726866,0.00005615205,0.9899606,0.0002415324,0.0004299489,0.007983742],"study_design_scores_gemma":[0.000009956101,0.0003064463,0.002335352,0.00001987512,0.0000338766,0.0002439899,0.0001505372,0.002295269,0.9911526,0.0001505682,0.003279095,0.00002245359],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8508828,0.006965802,0.1113818,0.001825104,0.0009884357,0.0001820523,0.0006958219,0.00161863,0.02545957],"genre_scores_gemma":[0.9167849,0.002294278,0.05559793,0.001232167,0.0001501504,0.0001361134,0.0002862029,0.00007374374,0.02344463],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003373652,"threshold_uncertainty_score":0.01128602,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01558593831601548,"score_gpt":0.1988814354097114,"score_spread":0.1832954970936959,"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."}}