{"id":"W4237434528","doi":"10.32920/ryerson.14667912","title":"Modelling The Transport and Return of Chloride Using INCA-Cl in an Urbanizing Watershed","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Smart Materials for Construction","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University; Statistics Canada; Toronto Metropolitan University; Memorial University of Newfoundland","funders":"","keywords":"Watershed; Aquatic ecosystem; Environmental science; Habitat; Ecosystem; Freshwater ecosystem; Chloride; Hydrology (agriculture); Environmental protection; Ecology; Fishery; Geography; Water resource management; Chemistry; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000383788,0.0001570523,0.0002426179,0.00003831646,0.00005316293,0.00004446086,0.0001794363,0.0001453565,0.0002509004],"category_scores_gemma":[0.00000372971,0.0001193796,0.00004215302,0.00008616311,0.0001530804,0.0002202083,0.0002925071,0.0002026756,9.987832e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001085231,"about_ca_system_score_gemma":0.00001759994,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01613485,"about_ca_topic_score_gemma":0.001771114,"domain_scores_codex":[0.9988339,0.0000595267,0.0003586109,0.0003874536,0.0001951592,0.0001653815],"domain_scores_gemma":[0.9994979,0.00001235629,0.0001163444,0.0003283553,0.000007569501,0.0000374864],"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":[0.00003256186,0.00001731671,0.3698432,0.0000560684,0.000009764924,0.000008075453,0.002966955,0.5374328,0.08954528,0.00001311635,4.725238e-7,0.00007430433],"study_design_scores_gemma":[0.0002803255,0.00001856024,0.03900769,0.0001926133,0.0000673691,0.00003991659,0.001619644,0.8139019,0.143368,0.001084878,0.00001890696,0.0004001342],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948688,0.00001994451,0.004367023,0.00003079967,0.0003071257,0.0002094439,0.00000340473,0.0000189905,0.0001745421],"genre_scores_gemma":[0.9942656,0.00002606784,0.005605957,0.00001629564,0.00003624094,0.000005095642,0.00001941399,0.00001702345,0.000008372093],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3308355,"threshold_uncertainty_score":0.9904168,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03307977352274566,"score_gpt":0.2303273114937999,"score_spread":0.1972475379710542,"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."}}