{"id":"W4211237123","doi":"10.1007/s11368-022-03157-4","title":"How to evaluate sediment fingerprinting source apportionments","year":2022,"lang":"en","type":"article","venue":"Journal of Soils and Sediments","topic":"Soil erosion and sediment transport","field":"Agricultural and Biological Sciences","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Environment and Protected Areas","funders":"Agence Nationale de la Recherche; Universität Basel","keywords":"Bayesian probability; Computer science; Residual; Environmental science; Mixing (physics); Statistics; Mathematics; Algorithm; Artificial intelligence; Physics","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":[0.0008332834,0.0001201888,0.0002013413,0.00003335134,0.0003682511,0.00008089602,0.0001910941,0.00002669274,0.0004085526],"category_scores_gemma":[0.00001748252,0.00005315931,0.000104054,0.000181539,0.00001573493,0.0001312602,0.0001199113,0.0001839134,0.000003840938],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005425274,"about_ca_system_score_gemma":0.00001189061,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001938209,"about_ca_topic_score_gemma":0.000002187604,"domain_scores_codex":[0.9983891,0.00006961446,0.0003456981,0.0001726085,0.0007930287,0.0002299038],"domain_scores_gemma":[0.9993608,0.00004328468,0.0002689901,0.00003666401,0.00006211406,0.0002281682],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003994095,0.0008225517,0.1258067,0.00001956876,0.0001919992,0.00007830667,0.001755069,0.0009220479,0.4223115,0.00004861694,0.009812859,0.4378314],"study_design_scores_gemma":[0.002665014,0.004094203,0.430063,0.0001100954,0.0001710768,0.0002133946,0.007804925,0.0006066736,0.0114737,0.00035122,0.5417371,0.0007095727],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948431,0.0001695172,0.00003499856,0.004242242,0.0004215406,0.0001325765,0.000007176895,0.00001188514,0.0001370144],"genre_scores_gemma":[0.9969942,0.00003598234,0.0001363557,0.001554078,0.0001842916,0.000009986364,0.000006593032,0.000001517232,0.001076996],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5319242,"threshold_uncertainty_score":0.4473364,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02481586168699967,"score_gpt":0.229733420684911,"score_spread":0.2049175589979113,"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."}}