{"id":"W2060062129","doi":"10.1007/s00181-010-0448-6","title":"Network externalities in consumer spending on lottery games: evidence from Spain","year":2010,"lang":"en","type":"article","venue":"Empirical Economics","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Lottery; Tobit model; Consumption (sociology); Economics; Externality; Consumer spending; Microeconomics; Consumer Expenditure Survey; Public economics; Advertising; Econometrics; Business; Macroeconomics; Sociology","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001373426,0.0003225433,0.0007475086,0.000245312,0.00010651,0.0002787414,0.0005082133,0.0002900978,0.002170646],"category_scores_gemma":[0.0003854888,0.0004070198,0.0001772317,0.0001319975,0.0001545696,0.0005181414,0.0001464327,0.0006906139,0.002768901],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000276326,"about_ca_system_score_gemma":0.00004316804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008157137,"about_ca_topic_score_gemma":0.00143362,"domain_scores_codex":[0.9972783,0.00003999156,0.00114899,0.0008372777,0.00002536482,0.0006701285],"domain_scores_gemma":[0.9977865,0.001008682,0.0004209559,0.0005814309,0.000008457207,0.0001940159],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001107318,0.00008257834,0.9689987,0.00001160636,0.00003529962,0.00001358241,0.0005110447,0.002188247,0.00001167154,0.02133374,0.002623741,0.00407902],"study_design_scores_gemma":[0.001551243,0.0001375369,0.4927518,0.0002178444,0.00001429925,0.00001232583,0.0001631354,0.0313925,0.00008225264,0.2836602,0.1883683,0.001648598],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9610358,0.000328319,0.000330936,0.00143092,0.002161386,0.0001797169,0.00007561113,0.0000601932,0.03439711],"genre_scores_gemma":[0.9930476,0.0008508578,0.00196832,0.002494036,0.001117228,0.00002363388,0.00001656792,0.00006715515,0.0004145944],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.476247,"threshold_uncertainty_score":0.9998382,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08886275030798725,"score_gpt":0.2742377315910977,"score_spread":0.1853749812831105,"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."}}