{"id":"W2362345958","doi":"","title":"Spatial Characteristics of Population Distribution and Its Evolution Tendency in Shanxi Province","year":2014,"lang":"en","type":"article","venue":"Resource Development & Market","topic":"Regional Economic and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Science North","funders":"","keywords":"Spatial distribution; Population; Population density; Geography; Distribution (mathematics); Spatial analysis; Spatial organization; Economies of agglomeration; Population size; Physical geography; Economic geography; Demography; Ecology; Mathematics; Remote sensing; Economic growth; Biology; Economics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007014594,0.0001106418,0.0003277269,0.0001601877,0.00005871127,0.00001949033,0.00009042418,0.00008126003,0.00009655324],"category_scores_gemma":[0.0001786661,0.0001273938,0.00003934579,0.000117612,0.00002003507,0.0001064165,0.00005083927,0.00006948313,0.00002218562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002095895,"about_ca_system_score_gemma":0.00002247049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000482522,"about_ca_topic_score_gemma":0.0001869144,"domain_scores_codex":[0.9987956,0.00003064766,0.0006845689,0.0002816496,0.00004471686,0.0001628149],"domain_scores_gemma":[0.9993824,0.00004257879,0.0003976122,0.0001077759,0.00002166651,0.00004795787],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006228504,0.00006283532,0.9451812,0.00007701685,0.00002633455,6.313421e-7,0.0001136983,0.00003331613,0.00000887437,0.03475136,0.0001663626,0.01951607],"study_design_scores_gemma":[0.0002355855,0.00001711427,0.9407842,0.00003122482,0.00000355309,9.271146e-7,0.00001078684,0.0365627,0.00001198592,0.001631126,0.0205655,0.0001452708],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9849594,0.0001647134,0.01092846,0.0002005757,0.00004678449,0.0001486967,0.00005699161,0.0000116144,0.003482794],"genre_scores_gemma":[0.9987241,0.00004454768,0.0001541196,0.0000241463,0.00004446594,0.00001103219,0.0002802757,0.000008378208,0.0007089229],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03652939,"threshold_uncertainty_score":0.5194966,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009246066875505827,"score_gpt":0.1748249485541798,"score_spread":0.1655788816786739,"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."}}