{"id":"W2154766867","doi":"10.1093/pan/mpq038","title":"Stochastic Process Methods with an Application to Budgetary Data","year":2010,"lang":"en","type":"article","venue":"Political Analysis","topic":"Income, Poverty, and Inequality","field":"Social Sciences","cited_by":86,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Quantile; Computer science; Econometrics; Variety (cybernetics); Process (computing); Stochastic process; Quantile regression; Distribution (mathematics); Variable (mathematics); Statistics; Mathematics; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.001630497,0.0001005409,0.0002487845,0.0001369515,0.0003212519,0.00008058341,0.0007312642,0.00008381254,0.0002573114],"category_scores_gemma":[0.0007507192,0.00007749511,0.00005278576,0.001192188,0.0002493219,0.0003181744,0.00007823205,0.0001765736,0.00004533969],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004360334,"about_ca_system_score_gemma":0.0001489748,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01932463,"about_ca_topic_score_gemma":0.02881142,"domain_scores_codex":[0.9981993,0.0002681258,0.0002031992,0.0004420305,0.0004131213,0.0004742212],"domain_scores_gemma":[0.9981091,0.0002254216,0.00004452537,0.0008395142,0.0002041159,0.0005773493],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003886748,0.0003103603,0.01505776,0.00001817149,0.0003257131,0.000001045304,0.002639821,0.0001413835,0.0001770405,0.9709498,0.00005934631,0.01028072],"study_design_scores_gemma":[0.0009696255,0.0006541676,0.1896108,0.00002215906,0.01130567,0.000004841545,0.02739556,0.3522427,0.0009324792,0.3757504,0.03818059,0.002931038],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1281427,0.000005604155,0.8470962,0.005463385,0.00007541226,0.0002497762,0.00009423416,0.0001084742,0.01876419],"genre_scores_gemma":[0.9775182,2.558934e-7,0.02062938,0.001143462,0.0004145507,0.00002581386,0.0001222039,0.000007330814,0.0001388267],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8493754,"threshold_uncertainty_score":0.9889103,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05694727340105604,"score_gpt":0.4483611952715523,"score_spread":0.3914139218704963,"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."}}