{"id":"W2366257123","doi":"","title":"Strategies and Inspiration of Drinking Water Source Protection in Canada","year":2007,"lang":"en","type":"article","venue":"China Water & Wastewater","topic":"Environmental and Agricultural Sciences","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Watershed; Water source; Watershed management; Business; Environmental planning; Environmental resource management; Water resources; Resource (disambiguation); Water resource management; Environmental science; Resource management (computing); Total maximum daily load; China; Groundwater; Engineering; Geography; Ecology; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002308488,0.000111234,0.00009625123,0.00002100917,0.0000838314,0.00003406664,0.00009676009,0.00003115242,0.0002988343],"category_scores_gemma":[6.730496e-7,0.0000502306,0.00001444102,0.00005340475,0.00009780729,0.0005398185,0.0001469243,0.00007922208,0.00002148008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001789511,"about_ca_system_score_gemma":0.000004468049,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.623669,"about_ca_topic_score_gemma":0.7043579,"domain_scores_codex":[0.9990182,0.00002126005,0.0002090937,0.0002153107,0.0002254604,0.0003106773],"domain_scores_gemma":[0.9998481,0.000002978017,0.00002660515,0.00007000976,0.000001407534,0.00005088713],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00001048368,0.00001434309,0.07216001,0.00000838281,0.000001512394,0.000004726994,0.002964939,0.002090707,0.9181558,0.000002522637,0.000005275391,0.004581244],"study_design_scores_gemma":[0.0001026539,0.00003508464,0.2942096,0.000009409558,0.000001755456,0.000006848004,0.00135868,0.00009171168,0.7032864,0.0001494406,0.0006484923,0.00009989726],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986275,0.000005704825,0.00005422942,0.0002103191,0.00005681582,0.0001611548,3.110222e-7,0.00000747441,0.0008765332],"genre_scores_gemma":[0.9995393,0.00000209414,0.00006414896,0.00003052732,0.00001795933,0.000005596848,0.000005326104,0.000004138489,0.0003308943],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2220496,"threshold_uncertainty_score":0.378837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005263942646195302,"score_gpt":0.1605862543509305,"score_spread":0.1553223117047352,"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."}}