{"id":"W1990999579","doi":"10.1016/s0304-3800(00)00390-2","title":"Evaluating modelling uncertainty for model selection","year":2001,"lang":"en","type":"article","venue":"Ecological Modelling","topic":"Groundwater flow and contamination studies","field":"Environmental Science","cited_by":109,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"Institute of Materials Research and Engineering","keywords":"Sensitivity (control systems); Closeness; Simple (philosophy); Computer science; Model selection; Selection (genetic algorithm); Errors-in-variables models; Propagation of uncertainty; Index (typography); Biological system; Econometrics; Mathematics; Algorithm; Machine learning; Engineering","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":[0.0005517749,0.0001490841,0.0001716562,0.00002534187,0.0005015795,0.00004147185,0.0001317754,0.00009303267,0.000338114],"category_scores_gemma":[0.00002645242,0.0001239234,0.00008860959,0.0001438972,0.00005008903,0.0001929415,0.00008333513,0.0001134048,0.00007847972],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002206694,"about_ca_system_score_gemma":0.000007958804,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005971151,"about_ca_topic_score_gemma":0.00004220927,"domain_scores_codex":[0.9986739,0.00003896239,0.000263264,0.0004099438,0.0002331931,0.0003807957],"domain_scores_gemma":[0.999601,0.0001366346,0.00006880555,0.00009151327,0.0000374263,0.0000646331],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003445787,0.00006036451,0.001010185,0.000002521024,0.000006999135,5.15031e-7,0.0001753855,0.9895526,0.0005044086,0.0004707806,0.00006362615,0.008118112],"study_design_scores_gemma":[0.0002997549,0.0001270959,0.00008770671,0.000003779388,0.0000188484,0.000002389486,0.00004862975,0.9855603,0.00007317134,0.01250175,0.001104865,0.0001717167],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4446529,0.00001047343,0.554155,0.00009366655,0.00003671966,0.0001969426,9.351429e-7,0.00005674488,0.0007965661],"genre_scores_gemma":[0.9056864,0.00002123462,0.09077586,0.0002168019,0.00005719337,0.0001663121,0.000006138092,0.00001140194,0.003058626],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4633791,"threshold_uncertainty_score":0.5053449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1248231236989422,"score_gpt":0.3183523890631133,"score_spread":0.1935292653641711,"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."}}