{"id":"W4386929710","doi":"10.56028/aehssr.7.1.297.2023","title":"Communication analysis of human mating behavior based on evolution","year":2023,"lang":"en","type":"article","venue":"Advances in Education Humanities and Social Science Research","topic":"Evolutionary Psychology and Human Behavior","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Mate choice; Selection (genetic algorithm); Mating; Spouse; Process (computing); Social evolution; Human communication; Social psychology; Psychology; Computer science; Communication; Biology; Evolutionary biology; Ecology; Sociology; Artificial intelligence","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":[0.0004787835,0.0001584852,0.0001408377,0.001385669,0.0004723301,0.0006676487,0.00020357,0.0002415935,0.002907245],"category_scores_gemma":[0.002595176,0.00007118566,0.0002994316,0.0008531307,0.0006456111,0.0006878407,0.0003445055,0.0002877964,0.0002530953],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004061646,"about_ca_system_score_gemma":0.0002214685,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00110136,"about_ca_topic_score_gemma":0.0005376532,"domain_scores_codex":[0.9996438,0.0001680323,0.00001725009,0.00006278998,0.00007637332,0.00003170787],"domain_scores_gemma":[0.999162,0.0004647201,0.0001145899,0.0000571866,0.0001524951,0.00004915634],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003174338,0.0001373988,0.1984897,0.0003812756,0.0001857243,0.001070663,0.007211626,0.02570938,0.02563573,0.4123865,0.003726425,0.324748],"study_design_scores_gemma":[0.0000222059,0.0003425479,0.5837713,0.0001403862,0.0001697644,0.003118646,0.003153561,0.1949888,0.00640852,0.1820211,0.02574241,0.0001207086],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7924719,0.003062194,0.1427651,0.001480646,0.0001523584,0.0001153053,0.0005298368,0.000150811,0.05927176],"genre_scores_gemma":[0.983536,0.0005714479,0.01278342,0.00005044677,0.00005849194,0.00003480155,0.0001347034,0.0000140657,0.002816608],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002907245,"threshold_uncertainty_score":0.00972569,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1699632876709665,"score_gpt":0.5414270993150184,"score_spread":0.3714638116440519,"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."}}