{"id":"W3006516459","doi":"10.1021/acsomega.9b04173","title":"DMN-Tre Labeling for Detection and High-Content Screening of Compounds against Intracellular Mycobacteria","year":2020,"lang":"en","type":"article","venue":"ACS Omega","topic":"Mycobacterium research and diagnosis","field":"Medicine","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Canadian Institutes of Health Research","keywords":"Intracellular; Mycobacterium tuberculosis; In vitro; Conjugate; Mycobacterium; Chemistry; Computational biology; Molecular biology; Biology; Tuberculosis; Microbiology; Biochemistry; Bacteria; Medicine; Genetics; 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":[0.0003240247,0.0005186798,0.0003347037,0.0003744015,0.0002446682,0.0002828967,0.0003994756,0.0007168436,0.002274088],"category_scores_gemma":[0.0004074164,0.0002421058,0.0002805179,0.0003184473,0.000297161,0.0004172883,0.0004267109,0.0008451568,0.0009066793],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000429531,"about_ca_system_score_gemma":0.0002530352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006745122,"about_ca_topic_score_gemma":0.002494663,"domain_scores_codex":[0.999627,0.00007753701,0.00001559564,0.0001060682,0.0001344224,0.00003935294],"domain_scores_gemma":[0.9998386,0.00004101544,0.00004133154,0.00002650167,0.00002918873,0.00002325273],"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":[0.0000313386,0.000009853891,0.00004917346,0.00005049854,0.000002763393,0.00001822193,0.000007254192,0.00004291596,0.9977596,0.0001532898,0.0000959933,0.001779268],"study_design_scores_gemma":[0.000003663119,0.00006168958,0.0002740373,0.000005449222,0.000004705422,0.0001553552,0.000006087527,0.0006073239,0.9957721,0.00005130284,0.003052706,0.00000545646],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5101117,0.01085074,0.4394686,0.0008774103,0.0003510401,0.0005455844,0.003881591,0.002004502,0.03190876],"genre_scores_gemma":[0.7454327,0.005744589,0.2246721,0.0005885099,0.00005845819,0.0004164002,0.004415176,0.0002580947,0.01841396],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002274088,"threshold_uncertainty_score":0.007607639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05716149037965465,"score_gpt":0.2710332672555198,"score_spread":0.2138717768758652,"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."}}