{"id":"W2041362059","doi":"10.1080/02724980443000160","title":"The Attraction Effect in Decision Making: Superior Performance by Older Adults","year":2004,"lang":"en","type":"article","venue":"The Quarterly Journal of Experimental Psychology Section A","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":108,"is_retracted":false,"has_abstract":true,"ca_institutions":"Baycrest Hospital; University of Toronto","funders":"National Institute on Aging","keywords":"Attraction; Psychology; Young adult; Domain (mathematical analysis); Developmental psychology; Heuristic; Social psychology; Cognitive psychology; Computer science; Artificial intelligence; Mathematics","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":[0.001109268,0.0002237047,0.0002341675,0.0004615929,0.0001797758,0.0005244191,0.0001204284,0.0004094599,0.003357604],"category_scores_gemma":[0.004210611,0.0001311155,0.0001373443,0.0001867202,0.0003491958,0.0007454214,0.0005186714,0.0003533434,0.0004356185],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009024183,"about_ca_system_score_gemma":0.0001029894,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001039613,"about_ca_topic_score_gemma":0.001052891,"domain_scores_codex":[0.999833,0.00002813104,0.00002007934,0.00004778908,0.00004799213,0.00002305621],"domain_scores_gemma":[0.9980587,0.0006341288,0.0006196315,0.0001498185,0.000158208,0.0003794174],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.002121541,0.0005755319,0.8879745,0.0001207271,0.0000653116,0.0006602821,0.005633341,0.0002555219,0.03888337,0.0008569919,0.0007569035,0.06209607],"study_design_scores_gemma":[0.0000195656,0.0005559453,0.9952833,0.000009107551,0.00001553857,0.0004191837,0.0003728891,0.000334387,0.001974084,0.0004746636,0.0005296735,0.00001169281],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985929,0.000122222,0.0001110297,0.00002899219,0.00000477668,0.00000389868,0.00003915688,0.000002753721,0.00109424],"genre_scores_gemma":[0.99901,0.0000776724,0.0001985344,0.00003459206,0.000009418842,0.000003600754,0.00005065092,0.000001642544,0.0006139402],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003357604,"threshold_uncertainty_score":0.01123238,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03219983119930698,"score_gpt":0.4113800543467117,"score_spread":0.3791802231474047,"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."}}