{"id":"W3216728843","doi":"","title":"District Census Handbook, Banas Kantha, Part XII A & B, Series-25","year":2016,"lang":"en","type":"article","venue":"Census Library, India","topic":"Rangeland Management and Livestock Ecology","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Geography; Population; Urban agglomeration; Socioeconomics; Quarter (Canadian coin); Rural area; Demography; Sociology; Political science; Archaeology; Law","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":[0.0005700961,0.0007468249,0.0005475727,0.004585461,0.0005529899,0.001416763,0.001526272,0.0003005633,0.1092575],"category_scores_gemma":[0.002953648,0.0007744639,0.0003016171,0.01628614,0.0002291097,0.001212053,0.0005087633,0.0009141659,0.05939183],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001694583,"about_ca_system_score_gemma":0.004436833,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.09430408,"about_ca_topic_score_gemma":0.08673672,"domain_scores_codex":[0.9994721,0.00008826097,0.00008970922,0.0001010027,0.0001882283,0.00006068906],"domain_scores_gemma":[0.998047,0.0002687976,0.0001714585,0.0001660705,0.001241033,0.0001056096],"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":[0.00002738222,0.00001548856,0.001666313,0.0003166021,0.00000821146,0.00002031556,0.0001078595,0.0002026785,0.00008648447,0.002134954,0.9706804,0.02473341],"study_design_scores_gemma":[0.00001573304,0.00001383,0.02255312,0.0001816216,0.000009722943,0.0000813416,0.000354522,0.0002143342,0.00008801359,0.0006248278,0.9758492,0.0000138984],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.003218831,0.004530807,0.001814769,0.001033783,0.001245208,0.0004721526,0.9123933,0.001049995,0.07424109],"genre_scores_gemma":[0.02302929,0.01117857,0.007732959,0.0006137925,0.00037405,0.001503952,0.7992851,0.0005721344,0.1557103],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1092575,"threshold_uncertainty_score":0.3655027,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009042680583219952,"score_gpt":0.1878780149082986,"score_spread":0.1788353343250787,"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."}}