{"id":"W3027579143","doi":"","title":"District Census Handbook, Ghazipur, Part XII-A & B, Vol-II, Series-10, Uttar Pradesh","year":2016,"lang":"en","type":"article","venue":"Census Library, India","topic":"South Asian Studies and Conflicts","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Census; Geography; Population; Socioeconomics; Uttar pradesh; Quarter (Canadian coin); Rural area; Demography; Sociology; Archaeology; Political science; 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":[0.0009550897,0.001625447,0.001109515,0.005737918,0.0008508108,0.001823611,0.002853884,0.000592134,0.100643],"category_scores_gemma":[0.004268174,0.001524201,0.0004992435,0.02212018,0.0004620293,0.002176846,0.0007134927,0.001841729,0.05620897],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002796831,"about_ca_system_score_gemma":0.008143386,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1230602,"about_ca_topic_score_gemma":0.09589004,"domain_scores_codex":[0.9992232,0.0001286115,0.0001804847,0.0001582787,0.0002228289,0.0000865234],"domain_scores_gemma":[0.9970019,0.0005070856,0.0002950091,0.0002690537,0.001764994,0.0001620177],"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":[0.00006474532,0.00006531751,0.003984625,0.0008987926,0.00001880176,0.00004257236,0.0003111738,0.0004285001,0.0001704173,0.001868409,0.9494221,0.04272451],"study_design_scores_gemma":[0.00009261184,0.00007260451,0.07410261,0.000474829,0.00002776223,0.0002070354,0.00114591,0.0003953167,0.0001948683,0.0009466677,0.9223049,0.00003493603],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.004452126,0.004810451,0.001222155,0.000905194,0.001125756,0.0009913498,0.9376156,0.001287841,0.04758951],"genre_scores_gemma":[0.02304955,0.01483229,0.01110912,0.0008201458,0.0005675165,0.003777585,0.8024464,0.0006918426,0.1427055],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1230602,"threshold_uncertainty_score":0.3366842,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02355336826905318,"score_gpt":0.2500425014475066,"score_spread":0.2264891331784534,"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."}}