{"id":"W3124354971","doi":"10.1016/j.chemosphere.2021.129781","title":"Quantitative screening for cyanotoxins in soil and groundwater of agricultural watersheds in Quebec, Canada","year":2021,"lang":"en","type":"article","venue":"Chemosphere","topic":"Aquatic Ecosystems and Phytoplankton Dynamics","field":"Environmental Science","cited_by":26,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; McGill University","funders":"China Scholarship Council; Fonds Québécois de la Recherche sur la Nature et les Technologies; Genome Canada","keywords":"Cyanotoxin; Environmental science; Groundwater; Vadose zone; Cylindrospermopsin; Environmental chemistry; Contamination; Hydrology (agriculture); Environmental engineering; Water resource management; Soil water; Microcystin; Ecology; Cyanobacteria; Biology; Soil science; Chemistry; Geology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0003351418,0.0003150117,0.0004143898,0.001582922,0.002094268,0.001143847,0.0007466485,0.0004417443,0.0009378644],"category_scores_gemma":[0.0007330134,0.0001902112,0.0001827055,0.003255241,0.000603994,0.0002564506,0.0003662717,0.000335276,0.0001618934],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0159321,"about_ca_system_score_gemma":0.01571884,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9892702,"about_ca_topic_score_gemma":0.9950336,"domain_scores_codex":[0.9993456,0.00004675028,0.00002778,0.0001272717,0.0002835798,0.0001691172],"domain_scores_gemma":[0.9988325,0.00008090573,0.0001142237,0.00001218341,0.0008334326,0.0001266919],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003506805,0.0002541163,0.8932845,0.0001968038,0.00009942647,0.0002928374,0.002379164,0.001718375,0.07221838,0.0003758745,0.001629312,0.02720059],"study_design_scores_gemma":[0.00001246497,0.0001064017,0.9883133,0.00002469725,0.00002811684,0.00005250603,0.002521707,0.001493852,0.00440505,0.00004441636,0.002982686,0.00001484241],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9927381,0.0004106485,0.0005731538,0.0001352648,0.000005760776,0.00008065331,0.003560057,0.00002225541,0.002473943],"genre_scores_gemma":[0.9930881,0.0003786129,0.001116795,0.00008019937,0.000002738684,0.00003207242,0.001892961,0.000005876429,0.003402734],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0159321,"threshold_uncertainty_score":0.1155961,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01025708707804678,"score_gpt":0.207412207931884,"score_spread":0.1971551208538372,"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."}}