{"id":"W4400512097","doi":"10.1002/bdm.2399","title":"When Half Is at Least 50%: Effect of “Framing” and Probability Level on Frequency Estimates","year":2024,"lang":"en","type":"article","venue":"Journal of Behavioral Decision Making","topic":"Forecasting Techniques and Applications","field":"Decision Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Defence Research and Development Canada","funders":"Ministère de la Défense Nationale","keywords":"Framing (construction); Econometrics; Statistics; Framing effect; Psychology; Mathematics; Economics; Social psychology; Geography","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.00390909,0.0002016926,0.0005102733,0.0004825643,0.0001652394,0.0003312495,0.0005982096,0.0001260499,0.0003274267],"category_scores_gemma":[0.001112156,0.0001243536,0.0002872195,0.0004572701,0.0001633315,0.000353127,0.0002453752,0.0003468758,0.00003266785],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001255273,"about_ca_system_score_gemma":0.00005942428,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002772187,"about_ca_topic_score_gemma":0.00001459101,"domain_scores_codex":[0.9965896,0.0001033638,0.001273535,0.0003984597,0.001437863,0.000197174],"domain_scores_gemma":[0.9958049,0.002615847,0.0006184198,0.0004669888,0.0003829687,0.0001108485],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002348438,0.0001360989,0.04283598,0.00004446516,0.00001371512,0.00006340894,0.0006104949,0.00006674937,0.008678873,0.001269972,0.009658796,0.9363866],"study_design_scores_gemma":[0.0009777471,0.005808161,0.09041595,0.005886418,0.0003662679,0.001443596,0.0001598089,0.01010718,0.02812576,0.8459273,0.01008115,0.0007006748],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9731655,0.0006014392,0.0251293,0.0003325809,0.0002712752,0.000231885,0.00003962643,0.00003400509,0.0001944628],"genre_scores_gemma":[0.8986863,0.00001045638,0.101117,0.00002353604,0.00005189461,0.000005985532,5.050213e-7,0.00001674318,0.00008761109],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9356859,"threshold_uncertainty_score":0.5070993,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1963843125055303,"score_gpt":0.4594626639077974,"score_spread":0.263078351402267,"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."}}