{"id":"W2095551648","doi":"10.1111/j.1467-8489.2009.00469.x","title":"Complexity in choice experiments: choice of the status quo alternative and implications for welfare measurement*","year":2009,"lang":"en","type":"article","venue":"Australian Journal of Agricultural and Resource Economics","topic":"Economic and Environmental Valuation","field":"Economics, Econometrics and Finance","cited_by":205,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; Commonwealth Scientific and Industrial Research Organisation","keywords":"Respondent; Status quo; Choice set; Preference; Welfare; Set (abstract data type); Task (project management); Status quo bias; Function (biology); Economics; Order (exchange); Econometrics; Psychology; Public economics; Microeconomics; Computer science; Political science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04558076,0.000813615,0.001442311,0.0007947315,0.0008714017,0.004062465,0.001039214,0.002199006,0.00453894],"category_scores_gemma":[0.1869043,0.0006447684,0.001390856,0.001258807,0.002933915,0.005660711,0.002603198,0.002705374,0.0004469246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001296417,"about_ca_system_score_gemma":0.0006962628,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005367486,"about_ca_topic_score_gemma":0.0007088553,"domain_scores_codex":[0.9535804,0.03695415,0.001995701,0.001836142,0.005019732,0.0006139308],"domain_scores_gemma":[0.6433963,0.2973942,0.03696268,0.01754452,0.002311059,0.002391158],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0539627,0.02851976,0.223846,0.003205448,0.00309814,0.0006652988,0.02117941,0.08524806,0.06785087,0.20135,0.003949499,0.3071248],"study_design_scores_gemma":[0.005184987,0.03190923,0.2321848,0.0005689104,0.0007405085,0.0004615471,0.002789334,0.2947647,0.02237292,0.3983168,0.009684067,0.001022156],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9534586,0.0001712842,0.03843821,0.0008826008,0.00005631964,0.001022871,0.0001839117,0.00003355484,0.005752495],"genre_scores_gemma":[0.9569592,0.000189059,0.03871648,0.0004090988,0.00007920587,0.002290215,0.0002342318,0.00001834005,0.001104162],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04558076,"threshold_uncertainty_score":0.241057,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1993201830507977,"score_gpt":0.2727111289171409,"score_spread":0.0733909458663432,"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."}}