{"id":"W4313856889","doi":"10.1016/j.tube.2023.102305","title":"Environmental risk of nontuberculous mycobacterial infection: Strategies for advancing methodology","year":2023,"lang":"en","type":"article","venue":"Tuberculosis","topic":"Mycobacterium research and diagnosis","field":"Medicine","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University Health Network","funders":"National Institute of Allergy and Infectious Diseases; National Institutes of Health","keywords":"Nontuberculous mycobacteria; Tuberculosis; Environmental health; Infectious disease (medical specialty); Medicine; Disease; Environmental resource management; Environmental planning; Geography; Mycobacterium; Pathology; Environmental science","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":[],"consensus_categories":[],"category_scores_codex":[0.0009195828,0.0001902487,0.0005036456,0.000259442,0.0001175978,0.00002236865,0.00007834188,0.0001514285,0.0007166819],"category_scores_gemma":[0.0007412691,0.0001694395,0.0003014793,0.0003106755,0.0001119222,0.0001749509,0.00008176621,0.0001752844,0.0001281006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009808239,"about_ca_system_score_gemma":0.0001126159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007518349,"about_ca_topic_score_gemma":0.0001029571,"domain_scores_codex":[0.9982794,0.0002252295,0.0003741485,0.0003377143,0.0002702892,0.0005132067],"domain_scores_gemma":[0.9982373,0.001049113,0.0001156835,0.0003320638,0.00005650602,0.0002093979],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001833495,0.0004252942,0.5055118,0.000910032,0.0009584799,0.00004144589,0.0009503702,0.0001806775,0.4438684,0.0005244942,0.009257218,0.03553834],"study_design_scores_gemma":[0.003128627,0.001985133,0.922493,0.0000996581,0.0007177266,0.00007031004,0.0008124812,0.0006912649,0.05711773,0.001815794,0.01074154,0.0003266735],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962817,0.0001073521,0.0009679705,0.0003474696,0.0004084639,0.000690575,0.0002918666,0.0001405217,0.000764075],"genre_scores_gemma":[0.99265,0.002378015,0.003787966,0.0001011067,0.0004686464,0.0002772694,0.0002052955,0.00003984591,0.00009190744],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4169813,"threshold_uncertainty_score":0.7847164,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03861689411903848,"score_gpt":0.3327602416638373,"score_spread":0.2941433475447988,"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."}}