{"id":"W1806059501","doi":"10.1002/bdm.1863","title":"When Does Framing Influence Preferences, Risk Perceptions, and Risk Attitudes? The Explicated Valence Account","year":2015,"lang":"en","type":"article","venue":"Journal of Behavioral Decision Making","topic":"Decision-Making and Behavioral Economics","field":"Decision Sciences","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; Defence Research and Development Canada","funders":"York University; Government of Canada; Defence Research and Development Canada","keywords":"Framing effect; Framing (construction); Prospect theory; Risk perception; Perception; Risk-seeking; Psychology; Valence (chemistry); Social psychology; Economics; Loss aversion; Positive economics; Microeconomics; Engineering; Chemistry","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.004486533,0.0004940477,0.0004136671,0.0007778999,0.0003799851,0.00331951,0.0004922738,0.001075977,0.002836454],"category_scores_gemma":[0.02399659,0.0004327624,0.0004436851,0.0003944325,0.002053436,0.002731047,0.001263552,0.001849111,0.0001882711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006702604,"about_ca_system_score_gemma":0.0003568419,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008183702,"about_ca_topic_score_gemma":0.0007279925,"domain_scores_codex":[0.9971411,0.001898955,0.0001005224,0.0002142077,0.0004791711,0.0001659924],"domain_scores_gemma":[0.9795442,0.01405729,0.002867675,0.001801065,0.00122381,0.0005060607],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.002991804,0.001534982,0.3220282,0.0008938838,0.0008660816,0.001264593,0.01416049,0.01399452,0.02339441,0.4741909,0.002448406,0.1422318],"study_design_scores_gemma":[0.0003149773,0.000788121,0.243856,0.0005186857,0.0006364037,0.0004715302,0.004972648,0.07444609,0.007457362,0.661824,0.004451546,0.0002626303],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9353369,0.0007487716,0.02366378,0.00217957,0.0001651929,0.00005556049,0.0001002005,0.00003324008,0.03771667],"genre_scores_gemma":[0.9974172,0.0001312479,0.001990366,0.0001152252,0.00003188258,0.00001487953,0.00002820675,0.000008148583,0.0002628002],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004486533,"threshold_uncertainty_score":0.0237273,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1262111218641538,"score_gpt":0.4200131924037594,"score_spread":0.2938020705396056,"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."}}