{"id":"W2037484203","doi":"10.1509/jmr.10.0250","title":"The Fewer the Better: Number of Goals and Savings Behavior","year":2011,"lang":"en","type":"article","venue":"Journal of Marketing Research","topic":"Behavioral Health and Interventions","field":"Psychology","cited_by":88,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Set (abstract data type); Goal pursuit; Contrast (vision); Computer science; Look-ahead; Psychology; Social psychology; 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.02207012,0.00006411493,0.0001391758,0.00008321107,0.0003669884,0.00003717234,0.0004334238,0.00007197828,0.002307207],"category_scores_gemma":[0.0008639124,0.00003329224,0.0001208149,0.000171179,0.000389615,0.00006956002,0.0001163914,0.0009526517,0.00003534057],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002870145,"about_ca_system_score_gemma":0.00005829528,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002842002,"about_ca_topic_score_gemma":0.00003373732,"domain_scores_codex":[0.9964923,0.001975249,0.0005597561,0.00009487149,0.000465011,0.0004128752],"domain_scores_gemma":[0.9969426,0.001828322,0.0002921516,0.0002528532,0.0005710696,0.0001129606],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001172199,0.0003185838,0.7629274,0.00002072709,0.00003978543,0.00003452494,0.001762131,3.369804e-9,0.000179553,0.0006676901,0.04268216,0.1901952],"study_design_scores_gemma":[0.0002966973,0.0002305762,0.9804612,0.0001100336,0.00002393886,0.0001768943,0.002145238,4.500248e-7,0.00005226427,0.0002653118,0.01620189,0.00003549417],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9833371,0.000805032,0.000002157599,0.00155567,0.0003545235,0.0001591401,0.000003047698,0.000002703981,0.01378061],"genre_scores_gemma":[0.9960061,0.0001603,0.000140126,0.00005507603,0.0001406924,0.00001782805,1.318707e-7,0.00001210384,0.003467652],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2175338,"threshold_uncertainty_score":0.9986048,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1990890514556373,"score_gpt":0.4986311688720854,"score_spread":0.2995421174164482,"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."}}