{"id":"W4388998814","doi":"10.1007/978-981-99-8132-8_32","title":"Federated Learning Using the Particle Swarm Optimization Model for the Early Detection of COVID-19","year":2023,"lang":"en","type":"book-chapter","venue":"Communications in computer and information science","topic":"COVID-19 diagnosis using AI","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"Brandon University","funders":"","keywords":"Computer science; Particle swarm optimization; Coronavirus disease 2019 (COVID-19); Process (computing); Convergence (economics); Artificial intelligence; Federated learning; Machine learning; Data mining","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":[0.001349799,0.0001000029,0.0001441282,0.0002226213,0.001050936,0.000185746,0.0004082053,0.00007095016,0.000001533637],"category_scores_gemma":[0.0004934467,0.00007183684,0.00004194162,0.0003953618,0.0006085832,0.0008182533,0.0003729469,0.0002648789,0.000002150191],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001981532,"about_ca_system_score_gemma":0.0005140314,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008142338,"about_ca_topic_score_gemma":0.00002577723,"domain_scores_codex":[0.9990299,0.00002787844,0.0004445873,0.0001176426,0.0002635127,0.0001165194],"domain_scores_gemma":[0.9976119,0.0009888306,0.0003073305,0.0005807995,0.0004573031,0.00005381734],"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":[0.00001471847,0.000007651925,0.00003610486,0.00005176526,0.00000869032,2.962279e-8,0.002831675,0.9786901,0.00002965142,0.004657161,0.00003459587,0.01363787],"study_design_scores_gemma":[0.0003179114,0.00004376293,0.0001319593,0.0001099663,0.00003568656,0.00000433681,0.00008376522,0.9933898,0.00004409232,0.0002768766,0.005490227,0.00007162655],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0005003346,0.00009616881,0.9917653,0.006444582,0.00007996969,0.0007261332,0.000006425028,0.00005552144,0.0003255693],"genre_scores_gemma":[0.9506714,0.002815692,0.0364129,0.008584398,0.00005603574,0.0001387321,0.00006915639,0.00003242752,0.001219197],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9553524,"threshold_uncertainty_score":0.8083057,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1533684044276493,"score_gpt":0.3783115203668231,"score_spread":0.2249431159391738,"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."}}