{"id":"W3132234976","doi":"","title":"District Census Handbook, Narmada, Part XII-A & B, Series-25","year":2016,"lang":"en","type":"article","venue":"Census Library, India","topic":"Eurasian Exchange Networks","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Geography; Population; Urban agglomeration; Socioeconomics; Quarter (Canadian coin); 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":[0.0006011738,0.0007838319,0.0006160702,0.00412445,0.0005405758,0.001374079,0.001534867,0.0003489845,0.1017994],"category_scores_gemma":[0.003505127,0.0008039936,0.0003208148,0.01601516,0.0002120169,0.001345371,0.0005407675,0.0009389396,0.05464602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001967662,"about_ca_system_score_gemma":0.004820549,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09157853,"about_ca_topic_score_gemma":0.08289189,"domain_scores_codex":[0.9994715,0.00009248659,0.00009812293,0.0000901291,0.0001858413,0.0000619007],"domain_scores_gemma":[0.9980208,0.0002589678,0.0001859575,0.0001483949,0.001283962,0.0001019211],"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":[0.0000356446,0.00002181792,0.002114266,0.0004501741,0.00001105665,0.00002572303,0.0001423998,0.0002513728,0.00009986931,0.002077181,0.9702441,0.02452647],"study_design_scores_gemma":[0.00002277341,0.00001841605,0.0339956,0.0002403028,0.00001337728,0.00008040918,0.0005904543,0.0002526362,0.0001047741,0.0006597125,0.9640062,0.00001521888],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003541411,0.003210878,0.001192573,0.000871766,0.0008729011,0.0005916015,0.9251823,0.0007729984,0.06376352],"genre_scores_gemma":[0.02474854,0.009850899,0.006911067,0.0005972733,0.0003224009,0.002405867,0.7873599,0.0004726768,0.1673313],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1017994,"threshold_uncertainty_score":0.340553,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02374852219486724,"score_gpt":0.25580785168788,"score_spread":0.2320593294930128,"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."}}