{"id":"W4200088307","doi":"10.4103/lungindia.lungindia_604_21","title":"Impact of COVID-19 pandemic on tuberculosis notifications in India","year":2021,"lang":"en","type":"letter","venue":"Lung India","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Medicine; Tuberculosis; Pandemic; Quarter (Canadian coin); Coronavirus disease 2019 (COVID-19); Government (linguistics); Public health; Contact tracing; Confidence interval; Environmental health; Demography; Disease; Infectious disease (medical specialty); Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001699741,0.0004031561,0.000286838,0.0007449932,0.0003649921,0.001352417,0.0006824869,0.0005480223,0.002275209],"category_scores_gemma":[0.009107769,0.0002572769,0.0007759813,0.0009605528,0.0003633406,0.0009343927,0.0009553991,0.001412675,0.0004730388],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002304712,"about_ca_system_score_gemma":0.001981555,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09007955,"about_ca_topic_score_gemma":0.06873848,"domain_scores_codex":[0.9986745,0.0003350558,0.0001451085,0.0002283835,0.000378867,0.0002381261],"domain_scores_gemma":[0.9967431,0.001358272,0.0009079045,0.0001880532,0.00050694,0.000295777],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003557317,0.0001713179,0.8481041,0.0002318146,0.0001349407,0.001198834,0.000879019,0.1042734,0.0007838586,0.002843735,0.01249985,0.02852365],"study_design_scores_gemma":[0.00002649474,0.0003851943,0.7051601,0.0003573662,0.0002301889,0.00150044,0.002004413,0.2731441,0.002068809,0.003522123,0.0114254,0.0001753825],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"editorial","genre_scores_codex":[0.962514,0.001574732,0.005458759,0.006416588,0.0004530334,0.00007775756,0.0121585,0.0006213167,0.01072536],"genre_scores_gemma":[0.9953496,0.0004593699,0.0007751822,0.0002956047,0.00007856894,0.00001267261,0.002550886,0.00003336389,0.0004448702],"genre_candidate":"editorial","genre_consensus":null,"teacher_disagreement_score":0.09007955,"threshold_uncertainty_score":0.1791105,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2180597705595746,"score_gpt":0.4479803663357839,"score_spread":0.2299205957762092,"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."}}