{"id":"W3135431006","doi":"","title":"District Census Handbook, Bhavnagar, 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; Urban agglomeration; Population; Socioeconomics; Quarter (Canadian coin); Urban district; Demography; Archaeology; Sociology; Environmental planning","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":[0.0007719951,0.0009669601,0.0008941925,0.005207493,0.0005834458,0.001563665,0.001920055,0.0003795888,0.08986633],"category_scores_gemma":[0.003614291,0.001050893,0.0003821292,0.02130326,0.000296965,0.001403187,0.0005935978,0.001227642,0.05991429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002205291,"about_ca_system_score_gemma":0.00508298,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1323715,"about_ca_topic_score_gemma":0.1058596,"domain_scores_codex":[0.9992124,0.0001518235,0.0001442157,0.0001471923,0.000256618,0.0000877894],"domain_scores_gemma":[0.9971233,0.0004295956,0.000250044,0.0002463398,0.001811453,0.00013929],"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":[0.00004374843,0.00002425141,0.002522576,0.0004781013,0.0000178948,0.00002516788,0.0001423187,0.0004101083,0.0001086851,0.002591139,0.966965,0.02667088],"study_design_scores_gemma":[0.00003538955,0.00003229417,0.04311393,0.00028397,0.00002090748,0.0001205287,0.0004831201,0.0003737549,0.0001387788,0.001023464,0.9543489,0.00002498101],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.003731166,0.005143613,0.001628846,0.0007476212,0.0009958073,0.0004296729,0.939186,0.0009241733,0.04721296],"genre_scores_gemma":[0.02200429,0.01041154,0.007346674,0.0005029531,0.0003456222,0.001248851,0.8570061,0.0005624755,0.1005715],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1323715,"threshold_uncertainty_score":0.3006328,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02005212723924537,"score_gpt":0.1921238839641389,"score_spread":0.1720717567248935,"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."}}