{"id":"W4389691994","doi":"10.1007/978-3-031-46359-4_5","title":"Social Human Collective Decision-Making and Its Applications with Brain Network Models","year":2023,"lang":"en","type":"book-chapter","venue":"Modeling and simulation in science, engineering & technology","topic":"Mental Health Research Topics","field":"Psychology","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Crowds; Computer science; Group decision-making; Inference; Artificial intelligence; Context (archaeology); Probabilistic logic; Social decision making; Bayesian inference; Population; Data science; Management science; Machine learning; Bayesian probability; Engineering; Psychology; Cognitive psychology; Computer security; Social psychology","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":[0.0007051377,0.0002149631,0.00030561,0.00142154,0.0005726739,0.00004680784,0.0002421666,0.0004445603,0.000009913683],"category_scores_gemma":[0.00006649576,0.0002242957,0.00001852785,0.0007718508,0.0002269266,0.0001027015,0.000184091,0.0006503019,0.000006075073],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002452346,"about_ca_system_score_gemma":0.0001130481,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006363618,"about_ca_topic_score_gemma":0.00002314568,"domain_scores_codex":[0.9981383,0.000009744331,0.0003702629,0.0006593592,0.0003313736,0.0004909263],"domain_scores_gemma":[0.9990892,0.000367476,0.00009173148,0.0002274828,0.0001516025,0.00007253577],"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":[0.00001004102,0.000003960348,0.00001309238,0.00001717963,0.000006664088,0.000003848641,0.000261052,0.6501865,0.000003612403,0.3446464,0.000006474565,0.004841173],"study_design_scores_gemma":[0.0002188003,0.00005485529,0.00003217915,0.0001838762,0.000005120796,0.000005020319,0.00003959016,0.8032719,2.80797e-7,0.1957233,0.0003004583,0.0001646118],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07222053,0.001617727,0.8700507,0.0007601283,0.0003252407,0.002964973,0.00002889352,0.001093401,0.05093838],"genre_scores_gemma":[0.9907899,0.0000186681,0.001820165,0.00002605674,0.00009828129,0.0001668376,0.000004487704,0.00005223081,0.007023395],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9185693,"threshold_uncertainty_score":0.9146512,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07141558058631195,"score_gpt":0.4016203401199713,"score_spread":0.3302047595336594,"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."}}