{"id":"W4386564056","doi":"10.5194/egusphere-2023-1970","title":"Sensitivity of source sediment fingerprinting modelling to tracer selection methods","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Soil erosion and sediment transport","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Environment and Protected Areas","funders":"Japan Society for the Promotion of Science; Centre National de la Recherche Scientifique; Commissariat à l'Énergie Atomique et aux Énergies Alternatives; Agence Nationale de la Recherche","keywords":"Sediment; TRACER; Context (archaeology); Selection (genetic algorithm); Tracing; Environmental science; Sensitivity (control systems); Soil science; Identification (biology); Linear discriminant analysis; Computer science; Geology; Artificial intelligence; Engineering; Geomorphology; Ecology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02412951,0.001625405,0.001112981,0.001615101,0.0006861946,0.00198367,0.00125002,0.001522701,0.0006152331],"category_scores_gemma":[0.05699357,0.0005593531,0.0014751,0.001043102,0.0008110738,0.001488659,0.002167671,0.00138475,0.0002928084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001118308,"about_ca_system_score_gemma":0.001254497,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01119739,"about_ca_topic_score_gemma":0.004220132,"domain_scores_codex":[0.9910082,0.005917213,0.0005171392,0.001359857,0.0009090711,0.00028857],"domain_scores_gemma":[0.9336745,0.05797479,0.002471337,0.003072648,0.002362897,0.0004438357],"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":[0.001724492,0.0002061811,0.07087172,0.000405464,0.0008497054,0.0001184019,0.0002604589,0.8490337,0.01025446,0.001963033,0.0005044271,0.06380799],"study_design_scores_gemma":[0.00003860877,0.0002616593,0.008767979,0.0000630303,0.0001130947,0.00006155026,0.00007075498,0.979776,0.00848923,0.00174627,0.0005601263,0.00005178362],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6551809,0.002465531,0.3376059,0.000473413,0.0001099117,0.0002482536,0.0007773059,0.001381703,0.001757028],"genre_scores_gemma":[0.9425162,0.0004383828,0.05498876,0.0001219313,0.00002407156,0.0001434369,0.00106089,0.0001731048,0.0005332615],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02412951,"threshold_uncertainty_score":0.1276106,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09772937608075515,"score_gpt":0.3147412058082104,"score_spread":0.2170118297274552,"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."}}