{"id":"W3199374451","doi":"10.1007/978-3-030-75668-0_11","title":"Sub-National Policy Impact in India: An Integrated Assessment","year":2021,"lang":"en","type":"book-chapter","venue":"","topic":"Income, Poverty, and Inequality","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Deliverable; Context (archaeology); Diversity (politics); Regional policy; Political science; Regional science; Business; Economic growth; Economics; Geography; Management","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007307265,0.0004096905,0.0004661293,0.002973515,0.001213875,0.004126854,0.0008442522,0.0004760911,0.004833445],"category_scores_gemma":[0.001505485,0.0002283215,0.0004931577,0.008614436,0.001754506,0.001787961,0.003025488,0.001403988,0.0004764852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008886999,"about_ca_system_score_gemma":0.00886214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06358349,"about_ca_topic_score_gemma":0.1402776,"domain_scores_codex":[0.9989356,0.000298562,0.00003177838,0.00005536304,0.0003403054,0.000338277],"domain_scores_gemma":[0.9991365,0.0004033697,0.00007363882,0.000056033,0.0002208235,0.0001097161],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.000278475,0.0002295232,0.0445056,0.0008509563,0.0001847979,0.0007709114,0.005189614,0.02514365,0.0008455343,0.6895995,0.02908258,0.2033188],"study_design_scores_gemma":[0.00002524104,0.0003845121,0.4943319,0.001024434,0.0004536808,0.0007897188,0.03308917,0.01913898,0.002347924,0.1900379,0.2582546,0.000121945],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.299189,0.02423654,0.002169454,0.00953106,0.0004168673,0.00006560473,0.00209516,0.0001529752,0.6621432],"genre_scores_gemma":[0.9464706,0.01733613,0.00168667,0.0005286016,0.0001305295,0.00007726664,0.0008287276,0.00005094677,0.03289047],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06358349,"threshold_uncertainty_score":0.1264268,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05479703844907197,"score_gpt":0.4030243512217736,"score_spread":0.3482273127727016,"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."}}