{"id":"W2084708041","doi":"10.1159/000365761","title":"Application of Three Focused Cluster Detection Methods to Study Geographic Variation in the Incidence of Multiple Sclerosis in Manitoba, Canada","year":2014,"lang":"en","type":"article","venue":"Neuroepidemiology","topic":"Data-Driven Disease Surveillance","field":"Medicine","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Multiple Sclerosis Society; Multiple Sclerosis Society of Canada; Manitoba Health Research Council; Health Sciences Centre Foundation","keywords":"Scan statistic; Incidence (geometry); Cluster (spacecraft); Medicine; Confounding; Geographic variation; Demography; Population; Socioeconomic status; Statistic; Cartography; Geography; Environmental health; Statistics; Pathology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.004998692,0.0007431259,0.0006065862,0.004098542,0.001514286,0.001196262,0.001852455,0.0004351452,0.0008218497],"category_scores_gemma":[0.0206067,0.0003158745,0.001093105,0.004908439,0.0005682072,0.0002169959,0.001381478,0.0004889969,0.00008540716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01140641,"about_ca_system_score_gemma":0.02677928,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9456008,"about_ca_topic_score_gemma":0.9441029,"domain_scores_codex":[0.9973428,0.001093194,0.0002175063,0.0005597344,0.0005404308,0.0002463362],"domain_scores_gemma":[0.9923361,0.002664481,0.0006763698,0.0004565087,0.00346893,0.0003975858],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002813642,0.00008951945,0.8662329,0.0002489285,0.001143359,0.0001945848,0.001665155,0.03186814,0.001085136,0.002208075,0.004347149,0.09063567],"study_design_scores_gemma":[0.0001231127,0.000112924,0.7681983,0.0001088287,0.0004243852,0.0001587776,0.002638118,0.2208449,0.0009257605,0.002184974,0.004183107,0.00009667635],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8986561,0.001093274,0.08817332,0.0007289913,0.00004729473,0.001137765,0.007170747,0.0004364974,0.00255605],"genre_scores_gemma":[0.8848143,0.000288993,0.1089385,0.0001007603,0.00001024763,0.0005297339,0.004372719,0.00003450269,0.0009102909],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05439919,"threshold_uncertainty_score":0.1094391,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05205174278524908,"score_gpt":0.3113736947226779,"score_spread":0.2593219519374288,"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."}}