{"id":"W2946517931","doi":"10.1101/639997","title":"Public health in genetic spaces: a statistical framework to optimize cluster-based outbreak detection","year":2019,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"HIV Research and Treatment","field":"Immunology and Microbiology","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Pairwise comparison; Cluster analysis; Covariate; Context (archaeology); Statistics; Population; Cluster (spacecraft); Null hypothesis; Range (aeronautics); Econometrics; Computer science; Data mining; Geography; Mathematics; Demography; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.01400932,0.001432893,0.002144466,0.003182068,0.001004865,0.002298545,0.00286699,0.002072508,0.001600659],"category_scores_gemma":[0.03145899,0.001140999,0.001846998,0.002212043,0.002674702,0.001762614,0.002717245,0.002703771,0.0002306888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004188838,"about_ca_system_score_gemma":0.004579675,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02256209,"about_ca_topic_score_gemma":0.01380685,"domain_scores_codex":[0.9938699,0.004534086,0.0001776519,0.0006605373,0.0004874264,0.0002704675],"domain_scores_gemma":[0.9827586,0.01312973,0.001263372,0.0006237645,0.001816064,0.0004084581],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002318426,0.00002527846,0.001037915,0.00001942338,0.00005481247,0.00002246127,0.000039077,0.9726021,0.0001153644,0.01943967,0.0004193851,0.006201384],"study_design_scores_gemma":[0.000004160653,0.000008597412,0.00008260778,0.000003191474,0.00000350771,0.000002242745,0.000005715352,0.9917607,0.00003294992,0.007991639,0.0001013873,0.000003367832],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01263526,0.0001338039,0.985694,0.000642807,0.00002369612,0.00006603947,0.0001093578,0.0001834187,0.0005116102],"genre_scores_gemma":[0.4246312,0.0002618558,0.57145,0.0003772332,0.0001908191,0.0005439125,0.0005553018,0.0002958425,0.001693743],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02256209,"threshold_uncertainty_score":0.07408923,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02810284611693186,"score_gpt":0.2646600657470059,"score_spread":0.236557219630074,"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."}}