{"id":"W2171484504","doi":"10.5210/ojphi.v3i2.3607","title":"Improving Agent Based Models and Validation through Data Fusion","year":2011,"lang":"en","type":"article","venue":"Online Journal of Public Health Informatics","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba; Orthopaedic Innovation Centre","funders":"","keywords":"Computer science; Data science; Bluetooth; Population; Granularity; Data mining; Agent-based model; Sensor fusion; Novelty; Robustness (evolution); Data aggregator; Machine learning; Artificial intelligence; Telecommunications; Wireless; Medicine; Wireless sensor network; Computer network","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.00864415,0.0001736392,0.0005666002,0.000138597,0.0001954951,0.00004821748,0.0005115684,0.00009633617,0.00003716175],"category_scores_gemma":[0.008550241,0.0001188912,0.00006088313,0.0001990823,0.00006623079,0.001790526,0.0004641227,0.0003849341,0.000001812831],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001925249,"about_ca_system_score_gemma":0.0006446842,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009517957,"about_ca_topic_score_gemma":0.00002465969,"domain_scores_codex":[0.9963741,0.0002567635,0.002408058,0.0001019431,0.0004583011,0.0004008392],"domain_scores_gemma":[0.9953256,0.0009056517,0.002600532,0.0004835796,0.0003897034,0.0002949025],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001711169,0.0034903,0.008639655,0.01009553,0.0004591779,0.00002338516,0.04948351,0.0008756966,0.0000187892,0.08534967,0.06743816,0.773955],"study_design_scores_gemma":[0.002247228,0.001222289,0.00204374,0.0004403607,0.00009291898,0.00008451878,0.005338616,0.8115038,0.00001775167,0.1279644,0.04861444,0.0004298979],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04807711,0.000255619,0.9424409,0.008383675,0.0001877891,0.0002603463,0.00009789301,0.00003901308,0.0002576704],"genre_scores_gemma":[0.113062,0.001179046,0.8788807,0.006588045,0.0001870272,0.000002280409,0.00007039016,0.00001806006,0.00001246964],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8106281,"threshold_uncertainty_score":0.9998012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.7488719034865434,"score_gpt":0.4974264133979003,"score_spread":0.2514454900886431,"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."}}