{"id":"W21767408","doi":"10.1186/1471-2288-11-108","title":"マクロ経済学入門 スポーツの経済効果をどのように測るか (特集 スポーツで入門! 経済学)","year":2013,"lang":"en","type":"article","venue":"経済セミナー = The keizai seminar","topic":"Housing Market and Economics","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institutes of Health Research","keywords":"Geography","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002212921,0.0002202718,0.0002832559,0.00152017,0.0006051172,0.00193493,0.0004858467,0.0004298585,0.02437164],"category_scores_gemma":[0.004547023,0.0001196738,0.0003374041,0.002316784,0.0007395275,0.001803807,0.0007347307,0.0005713737,0.006546217],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008586908,"about_ca_system_score_gemma":0.0006594405,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003828439,"about_ca_topic_score_gemma":0.005874735,"domain_scores_codex":[0.9993014,0.0002038337,0.00007994142,0.0001143542,0.0002413808,0.0000590269],"domain_scores_gemma":[0.9981613,0.0004659077,0.0003592833,0.0001055479,0.0007900887,0.0001179959],"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":[0.0004758011,0.0002408175,0.1449419,0.0009560682,0.000130479,0.0003543665,0.002827846,0.001493009,0.004355622,0.1867023,0.1056062,0.5519156],"study_design_scores_gemma":[0.00006760158,0.0005444197,0.4495809,0.0004397771,0.0001339346,0.001090277,0.005744211,0.009929105,0.008979697,0.09776867,0.4254681,0.0002532907],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4276811,0.004199406,0.09937021,0.01707914,0.004558969,0.0008936823,0.02198859,0.0009105132,0.4233184],"genre_scores_gemma":[0.8294804,0.001938017,0.04099451,0.0005363316,0.000976759,0.0004817114,0.005971816,0.000137857,0.1194826],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02437164,"threshold_uncertainty_score":0.08153129,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01912205533883328,"score_gpt":0.1795811306355694,"score_spread":0.1604590752967361,"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."}}