{"id":"W3133765840","doi":"","title":"District Census Handbook, Kheda, Part XII-A & B, Series-25","year":2016,"lang":"en","type":"article","venue":"Census Library, India","topic":"Agricultural Economics and Practices","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Geography; Population; Urban agglomeration; Socioeconomics; Quarter (Canadian coin); Population statistics; Demography; Archaeology; Sociology","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":[0.000630133,0.0007781375,0.0006615306,0.004015401,0.0004482902,0.001320468,0.001465999,0.0003260626,0.1054267],"category_scores_gemma":[0.003314356,0.0007814576,0.0003333052,0.01594937,0.0002079993,0.001285335,0.0004687823,0.0008638054,0.06360224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001704786,"about_ca_system_score_gemma":0.004265508,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08320884,"about_ca_topic_score_gemma":0.06944402,"domain_scores_codex":[0.9994382,0.00009263755,0.0001034645,0.0001063809,0.0001930753,0.00006615566],"domain_scores_gemma":[0.9978624,0.0002670912,0.0001892501,0.0001718262,0.00140236,0.0001071126],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003615618,0.00001696844,0.002272783,0.0004299335,0.00001164358,0.00001767539,0.00008865476,0.0002322709,0.00007330866,0.001576343,0.9747666,0.02047777],"study_design_scores_gemma":[0.00003094617,0.0000194327,0.03222807,0.0002318753,0.00001526682,0.00007558426,0.0004078289,0.0002524502,0.0001023232,0.0006301217,0.9659901,0.00001594594],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.002193414,0.002438486,0.001105049,0.0004739259,0.0007830338,0.000411469,0.9485356,0.0006346924,0.0434242],"genre_scores_gemma":[0.01739261,0.006944709,0.005068512,0.0004466222,0.0002739787,0.001440909,0.8697494,0.0003646841,0.09831856],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1054267,"threshold_uncertainty_score":0.3526874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02044986286757085,"score_gpt":0.1932864590120047,"score_spread":0.1728365961444338,"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."}}