{"id":"W6920379952","doi":"10.6068/dp14cf2a7411280","title":"Ranking of Countries (2010). Organisation for Economic Co-operation and Development (OECD). OECD Factbook 2014: Economic, Environmental and Social Statistics: Environment - Water Consumption | Socioeconomic Indicator: Water Abstractions per Capita, 2010. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 062-001-025.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Per capita; Water use; Hydroelectricity; Surface water; Consumption (sociology); Socioeconomic status; Economic data; Ranking (information retrieval)","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":[0.00166244,0.002755921,0.002739264,0.008982575,0.0008450706,0.004186017,0.002380467,0.001283181,0.07870357],"category_scores_gemma":[0.012201,0.001089103,0.001616483,0.03807552,0.0004707229,0.003167255,0.002192565,0.003269652,0.124174],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003187801,"about_ca_system_score_gemma":0.006511755,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1041307,"about_ca_topic_score_gemma":0.06384506,"domain_scores_codex":[0.9969097,0.0004041257,0.0006112864,0.0006901874,0.0009257426,0.0004589056],"domain_scores_gemma":[0.9926072,0.001024853,0.0007864999,0.0006253417,0.004623105,0.0003329734],"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":[0.00001826866,0.000007863619,0.0005739367,0.0004854857,0.00001987295,0.000009632437,0.00001214566,0.0001106597,0.00001969001,0.0005313899,0.996353,0.001858102],"study_design_scores_gemma":[0.00008786342,0.00001228321,0.008383828,0.0007237939,0.00003144169,0.00002719173,0.0001794987,0.0001324496,0.0001024781,0.0007622253,0.9895272,0.00002973083],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00004862484,0.00008663968,0.00002662719,0.00005570358,0.00004106083,0.000008125553,0.9988481,0.00004750519,0.0008375032],"genre_scores_gemma":[0.0003588078,0.0002742615,0.0002401491,0.00005444433,0.00001581122,0.00009775915,0.9977461,0.00006378617,0.001148842],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1041307,"threshold_uncertainty_score":0.2632897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03162004994726641,"score_gpt":0.2581432593453437,"score_spread":0.2265232093980773,"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."}}