{"id":"W156569066","doi":"10.3233/978-1-60750-028-5-399","title":"An Evaluation of Sociocultural Data for Predicting Attitudinal Tendencies","year":2009,"lang":"en","type":"book-chapter","venue":"Frontiers in artificial intelligence and applications","topic":"Cultural Differences and Values","field":"Psychology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Computer Research Institute of Montréal; McGill University","funders":"","keywords":"Sociocultural evolution; Psychology; Social psychology; Sociology; Anthropology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0101448,0.0007706819,0.0004476671,0.003156059,0.0004558346,0.001386243,0.0006731427,0.0006228692,0.002570513],"category_scores_gemma":[0.04067687,0.0001700695,0.0006555382,0.003750297,0.0003591358,0.00155102,0.001061204,0.0008615342,0.001253389],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004251694,"about_ca_system_score_gemma":0.0003899587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002901048,"about_ca_topic_score_gemma":0.005182783,"domain_scores_codex":[0.9938803,0.004470441,0.0002448021,0.0002470079,0.001057396,0.000100007],"domain_scores_gemma":[0.9277045,0.0589452,0.001811536,0.004677946,0.006143267,0.0007175726],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006820993,0.000842051,0.7430742,0.0002617889,0.000299944,0.0001865352,0.001911724,0.007210292,0.001546289,0.003643807,0.004056327,0.236285],"study_design_scores_gemma":[0.0001062727,0.001489038,0.8310615,0.0003643383,0.0002972071,0.0004705374,0.005066006,0.1337248,0.005716965,0.007339159,0.01423455,0.0001297498],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9350594,0.0008062079,0.03156462,0.0003955571,0.000133242,0.0005030913,0.0052462,0.0003896608,0.02590209],"genre_scores_gemma":[0.9569036,0.0003738361,0.0351001,0.00006155285,0.0000450858,0.0005836171,0.004387759,0.00005720992,0.002487202],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0101448,"threshold_uncertainty_score":0.05365145,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3455913780565109,"score_gpt":0.4473497720735106,"score_spread":0.1017583940169998,"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."}}