{"id":"W6942751775","doi":"10.15456/jae.2022327.0707051634","title":"Flexible Estimation of Demand Systems: A Copula Approach (replication data)","year":2018,"lang":"en","type":"other","venue":"ZBW Journal Data Archive","topic":"Mycorrhizal Fungi and Plant Interactions","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bank of Canada","funders":"","keywords":"Almost ideal demand system; Copula (linguistics); Bayesian probability; Estimation; Quadratic equation; Skewness; Price elasticity of demand; Budget constraint; Elasticity (physics)","routes":{"ca_aff":true,"ca_fund":false,"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":[0.02656653,0.0009081959,0.001437662,0.001823977,0.001055329,0.001959976,0.003418808,0.001528606,0.004537542],"category_scores_gemma":[0.1231644,0.0009421715,0.003187225,0.003954466,0.001159705,0.002472503,0.002248125,0.002582933,0.001257107],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001565122,"about_ca_system_score_gemma":0.001771967,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06465589,"about_ca_topic_score_gemma":0.03283652,"domain_scores_codex":[0.9773043,0.01693418,0.0007574912,0.00301069,0.001474479,0.0005188973],"domain_scores_gemma":[0.9109353,0.03813921,0.006830629,0.03578031,0.00775783,0.000556772],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008410429,0.0006678852,0.4002908,0.0007886459,0.003875269,0.001400716,0.004863927,0.3346419,0.002079971,0.08979136,0.02017578,0.1405827],"study_design_scores_gemma":[0.00023415,0.0003855066,0.08445363,0.0001851841,0.0005661362,0.0005849409,0.001811974,0.8243179,0.001870028,0.06506836,0.02027558,0.0002466174],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"dataset","genre_scores_codex":[0.4597813,0.001084311,0.5226015,0.001274231,0.0002003284,0.0007206045,0.007617269,0.0007145863,0.006005831],"genre_scores_gemma":[0.8790966,0.0002038603,0.1113195,0.0002221658,0.00008204424,0.0005445618,0.006690492,0.0002188875,0.001621917],"genre_candidate":"dataset","genre_consensus":null,"teacher_disagreement_score":0.06465589,"threshold_uncertainty_score":0.1404989,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06328617324789836,"score_gpt":0.2886645605111344,"score_spread":0.2253783872632361,"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."}}