{"id":"W4254064192","doi":"10.4095/300919","title":"Service Industries: Per Capita Income, 1996","year":2010,"lang":"en","type":"report","venue":"","topic":"Economic Theory and Policy","field":"Economics, Econometrics and Finance","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Per capita income; Per capita; Service (business); Business; Agricultural economics; Economics; Marketing; Demography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0005691631,0.001856395,0.0005994207,0.006477235,0.0003859423,0.001413456,0.0009982692,0.0004517609,0.02993104],"category_scores_gemma":[0.002061003,0.0004532203,0.0004323328,0.01489822,0.0002600991,0.001604271,0.0008227187,0.001386021,0.03453681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003012071,"about_ca_system_score_gemma":0.001645266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1117739,"about_ca_topic_score_gemma":0.07145089,"domain_scores_codex":[0.9992707,0.00005632439,0.00009942002,0.00009469225,0.0003799504,0.00009882618],"domain_scores_gemma":[0.9990114,0.0000747891,0.0001324413,0.00004370296,0.0006843485,0.0000533386],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001569078,0.00007450421,0.01555347,0.0006305577,0.00004574819,0.00007291032,0.0001775849,0.000847327,0.0001592145,0.003460119,0.9413565,0.03746513],"study_design_scores_gemma":[0.00004627805,0.00005343982,0.1594543,0.0002771323,0.00002179052,0.0001447633,0.0004299895,0.000479809,0.0003140997,0.0009072453,0.8378451,0.00002605144],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.005347977,0.00192954,0.0003202021,0.0005012247,0.0003796376,0.0001007322,0.9456407,0.0003525132,0.04542745],"genre_scores_gemma":[0.02714159,0.004839701,0.00123811,0.0001349322,0.0001266243,0.0004350712,0.8999832,0.0001374838,0.06596331],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1117739,"threshold_uncertainty_score":0.2222466,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05528952770441331,"score_gpt":0.2587306578359333,"score_spread":0.20344113013152,"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."}}