{"id":"W7008469750","doi":"","title":"CANADIAN/UNITED STATES DATA CONVERSION TABLES","year":2017,"lang":"en","type":"article","venue":"AgEcon Search (University of Minnesota, USA)","topic":"Census and Population Estimation","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Data conversion; Table (database); Data system; State (computer science); Data collection","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0005010045,0.00009354536,0.0001758059,0.0002570042,0.0008038131,0.00004623979,0.000872522,0.00008272215,0.002038118],"category_scores_gemma":[0.000187642,0.0001137736,0.00003668047,0.0001005345,0.0001556674,0.0007506651,0.000313259,0.0001131828,0.0001389079],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009489147,"about_ca_system_score_gemma":0.0001396021,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.4039706,"about_ca_topic_score_gemma":0.3375442,"domain_scores_codex":[0.9991218,0.00006193038,0.0001094887,0.000226688,0.0002312793,0.0002487593],"domain_scores_gemma":[0.9981968,0.0001758412,0.0001694057,0.001051487,0.0002071764,0.0001992818],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0002779954,0.0003688154,0.3467897,0.001125491,0.0004341828,0.0004613519,0.01181384,0.0003313726,0.000662288,0.0533188,0.5412132,0.04320296],"study_design_scores_gemma":[0.003146017,0.0001599109,0.3724009,0.0002451597,0.0002064348,0.00002025083,0.007855084,0.2389376,0.0004232766,0.007542424,0.3683121,0.0007508338],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9921213,0.00001346158,0.0009005314,0.003458202,0.00008326804,0.0001745766,0.0006935272,0.00001842919,0.002536742],"genre_scores_gemma":[0.9881202,0.0001500871,0.005223385,0.00004397525,0.00002511306,7.977838e-8,0.001357156,0.00001144539,0.005068552],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2386062,"threshold_uncertainty_score":0.9988741,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.139557589640005,"score_gpt":0.3274579100697681,"score_spread":0.1879003204297631,"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."}}