{"id":"W4399963442","doi":"10.1093/pnasnexus/pgae232","title":"Valuations of target items are drawn towards unavailable decoy items due to prior expectations","year":2024,"lang":"en","type":"article","venue":"PNAS Nexus","topic":"Multi-Criteria Decision Making","field":"Decision Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Science Foundation","keywords":"Decoy; Computer science; Psychology; Medicine; Internal medicine","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":[0.003302838,0.0004782767,0.0005429063,0.0004733212,0.0005178301,0.002272901,0.0004471247,0.0008189806,0.005256866],"category_scores_gemma":[0.02325504,0.000773794,0.0007622387,0.000291008,0.0009910577,0.002546992,0.001456089,0.001922313,0.0005454942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005544831,"about_ca_system_score_gemma":0.0002839973,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00112663,"about_ca_topic_score_gemma":0.001172077,"domain_scores_codex":[0.9972231,0.0009252489,0.0001930674,0.0007047695,0.0007587264,0.0001950938],"domain_scores_gemma":[0.9862131,0.008456061,0.001747956,0.002046893,0.0008990217,0.0006369404],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.006583698,0.0008325435,0.4514672,0.001649373,0.0009864203,0.001669494,0.01124352,0.0112603,0.3103472,0.03976178,0.001722975,0.1624756],"study_design_scores_gemma":[0.0002487274,0.001727271,0.8814005,0.0002720692,0.0004573934,0.001261921,0.00331514,0.02743787,0.02743728,0.05142639,0.004809516,0.0002058839],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9782054,0.0002729139,0.01265892,0.0001853986,0.00002809356,0.0000478942,0.00004499591,0.00003327147,0.008523274],"genre_scores_gemma":[0.9952231,0.0001278157,0.003713893,0.0001106157,0.00001427292,0.0000407665,0.00006304731,0.00002370829,0.0006829078],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005256866,"threshold_uncertainty_score":0.01758593,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1874607206854822,"score_gpt":0.4552383851139726,"score_spread":0.2677776644284904,"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."}}