{"id":"W1619090422","doi":"10.1016/j.foodpol.2015.08.002","title":"Urban land expansion in India 1992–2012","year":2015,"lang":"en","type":"article","venue":"Food Policy","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":50,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Solar Energy Technologies Office","keywords":"Urban agglomeration; Geography; Woodland; Urban expansion; Census; Quarter (Canadian coin); Land use; Food security; Land cover; Agricultural economics; Economic growth; Economics; Economic geography; Population; Urbanization; Agriculture; Ecology; 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001193923,0.0000717161,0.00008744988,0.00004776596,0.00002505148,0.00001628862,0.0001354848,0.00005082547,0.0002016519],"category_scores_gemma":[0.00000871572,0.00005445321,0.00001655489,0.0002225008,0.000006465224,0.0002201942,0.00009952271,0.00004909962,0.001432369],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008365537,"about_ca_system_score_gemma":0.0000172222,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007662625,"about_ca_topic_score_gemma":0.007803064,"domain_scores_codex":[0.9993839,0.00002726612,0.0001050419,0.0001273506,0.0001386445,0.0002177726],"domain_scores_gemma":[0.9996758,0.000008346039,0.00002924996,0.0001521865,0.000001416865,0.0001329994],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001406439,0.00005121373,0.9813227,0.00000997335,0.00000385611,0.000005368158,0.002133077,0.00009219493,0.0000946079,0.0001035168,0.0152323,0.0009371515],"study_design_scores_gemma":[0.0009779003,0.0002563985,0.8505552,0.00002590376,0.000004673966,0.000009417322,0.0001274791,0.0002570424,0.0005287754,0.001083348,0.1459445,0.0002293204],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9609253,0.00008107571,8.092077e-7,0.0003169328,0.00006717516,0.00007442556,0.000007396524,0.00002179097,0.03850503],"genre_scores_gemma":[0.999242,0.000006036887,0.00002262513,0.0003880523,0.0001971414,0.000007891085,0.000007089535,0.000007288764,0.0001218749],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1307674,"threshold_uncertainty_score":0.9993451,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01705446189511919,"score_gpt":0.2370086715033253,"score_spread":0.2199542096082061,"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."}}