{"id":"W2915249159","doi":"10.1051/matecconf/201927004017","title":"Association rules and regression linear model of the groundwater population by the evaluation of uranium","year":2019,"lang":"en","type":"article","venue":"MATEC Web of Conferences","topic":"Data Mining Algorithms and Applications","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Alkalinity; Linear regression; Uranium; Regression analysis; Variables; Population; Groundwater; Variable (mathematics); Statistics; Regression; Mathematics; Linear model; Chemistry; Geology; Demography; Materials science; Metallurgy","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":[],"consensus_categories":[],"category_scores_codex":[0.0007241652,0.00004840981,0.00009738114,0.00002161994,0.00004406192,0.00002810424,0.0003253448,0.00003741653,0.00001083844],"category_scores_gemma":[0.00003064924,0.0000251196,0.00002065412,0.00008473248,0.00002995832,0.0001718655,0.0000894311,0.00003750177,0.000001389633],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001093972,"about_ca_system_score_gemma":0.000089715,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002815349,"about_ca_topic_score_gemma":0.00001549897,"domain_scores_codex":[0.9991696,0.00007648799,0.0001917852,0.0001057303,0.0004023901,0.00005397579],"domain_scores_gemma":[0.9991283,0.00006220801,0.0003321092,0.0002560854,0.0002135755,0.000007752775],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002730868,0.0003578612,0.2871115,0.0002563022,0.0001559908,2.054828e-8,0.003694125,0.005020639,0.1428302,0.2574438,0.00335342,0.2997488],"study_design_scores_gemma":[0.00014366,0.00001973464,0.04907894,0.00004681579,0.00002063318,1.783031e-7,0.00005557827,0.9328908,0.01169034,0.005913326,0.0001034455,0.00003651387],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9920804,0.00005454446,0.006087117,0.0007559294,0.00006475589,0.0001826089,0.00003018655,0.000007848701,0.0007366122],"genre_scores_gemma":[0.9978258,0.0000163044,0.001958952,0.000009584037,0.000005609806,0.000007780252,0.00001426245,0.000001717712,0.000160002],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9278702,"threshold_uncertainty_score":0.1024347,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03618156327705389,"score_gpt":0.2820764682358498,"score_spread":0.2458949049587958,"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."}}