{"id":"W3174942162","doi":"10.1101/2021.06.25.449992","title":"Use of untargeted magnetic beads to capture <i>Mycobacterium smegmatis</i> and <i>Mycobacterium avium paratuberculosis</i> prior detection by mycobacteriophage D29 and Real-Time-PCR","year":2021,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"Mycobacterium research and diagnosis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; University of Alberta","funders":"Alberta Agriculture and Forestry","keywords":"Mycobacterium smegmatis; Centrifugation; Urine; Mycobacterium; Feces; Microbiology; Chromatography; Biology; Paratuberculosis; Chemistry; Virology; Bacteria; Medicine; Mycobacterium tuberculosis; Biochemistry; Pathology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006211974,0.0008051743,0.0006602303,0.0003358883,0.000163258,0.0006608107,0.0005802678,0.0007828022,0.0007404184],"category_scores_gemma":[0.0009596336,0.0003971355,0.0004518112,0.0001638316,0.0004162182,0.0003117432,0.0005259572,0.0005252851,0.0004643161],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000295187,"about_ca_system_score_gemma":0.0002338197,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005884996,"about_ca_topic_score_gemma":0.001243294,"domain_scores_codex":[0.9989499,0.0001786355,0.00008494665,0.0002975106,0.0003512772,0.0001376881],"domain_scores_gemma":[0.999391,0.0002151622,0.000157001,0.00007703804,0.0001128391,0.00004696915],"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":[0.0000291545,0.0000162638,0.0002465128,0.00003692165,0.00000505256,0.00001096719,0.000007743038,0.00004978563,0.9985576,0.000008640536,0.00001610378,0.001015358],"study_design_scores_gemma":[0.000004837812,0.0002896464,0.003110791,0.000007595566,0.00002198999,0.0001009946,0.00001559065,0.001245504,0.9945076,0.0000150062,0.0006709665,0.000009586616],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9188851,0.002059972,0.07646398,0.0001879485,0.0001348477,0.0001786703,0.0003461166,0.0005588495,0.001184558],"genre_scores_gemma":[0.924975,0.0007632819,0.07030397,0.0003024041,0.00003938081,0.000172114,0.000733598,0.00008249115,0.002627774],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008051743,"threshold_uncertainty_score":0.003285229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009924831875841332,"score_gpt":0.2207427066856205,"score_spread":0.2108178748097792,"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."}}