{"id":"W1963966879","doi":"10.1080/02626667.2014.900558","title":"A new fuzzy linear regression approach for dissolved oxygen prediction","year":2014,"lang":"en","type":"article","venue":"Hydrological Sciences Journal","topic":"Fuzzy Systems and Optimization","field":"Mathematics","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Natural Sciences and Engineering Research Council of Canada; University of Victoria","keywords":"Fuzzy logic; Linear regression; Mathematics; Regression; Regression analysis; Data mining; Computer science; Mathematical optimization; Statistics; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009742382,0.0007640204,0.001011852,0.001072492,0.0003655785,0.000768613,0.001476398,0.0007851548,0.001818689],"category_scores_gemma":[0.002161137,0.0003585004,0.0009671794,0.000964176,0.0003651428,0.001101356,0.0006200203,0.001456496,0.0006459265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006295858,"about_ca_system_score_gemma":0.0008312394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004930947,"about_ca_topic_score_gemma":0.005482323,"domain_scores_codex":[0.9991373,0.0001869286,0.0000492749,0.0002314304,0.0003611037,0.00003383802],"domain_scores_gemma":[0.9993629,0.0002776659,0.00005398932,0.00003439578,0.0002528893,0.00001814657],"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":[0.00009640554,0.0001148073,0.001599595,0.0004381576,0.0002130227,0.0003000488,0.0002573404,0.3448096,0.02925092,0.03034947,0.003857556,0.5887132],"study_design_scores_gemma":[0.000009353091,0.00004468131,0.0002174913,0.00001128253,0.0000180006,0.00007208974,0.00001429272,0.9909251,0.002070787,0.002738223,0.003855175,0.00002339474],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001807047,0.0002486991,0.9970425,0.00005326466,0.00005708489,0.00001640413,0.00002050661,0.000127868,0.0006266365],"genre_scores_gemma":[0.1121092,0.0008865499,0.8796799,0.00010721,0.0001588874,0.0001974133,0.0001370853,0.00008081993,0.006642901],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004930947,"threshold_uncertainty_score":0.009804487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.071652510659346,"score_gpt":0.3171140977166065,"score_spread":0.2454615870572605,"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."}}