{"id":"W4210609173","doi":"10.1016/j.jglr.2022.01.013","title":"Characteristics of nearshore water quality of Lake Ontario coast under Credit Valley Conservation Jurisdiction, Ontario, Canada","year":2022,"lang":"en","type":"article","venue":"Journal of Great Lakes Research","topic":"Water Quality and Pollution Assessment","field":"Environmental Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Guelph; Credit Valley Hospital","funders":"Environment and Climate Change Canada","keywords":"Environmental science; Water quality; Hydrology (agriculture); Downwelling; Tributary; Oceanography; Fishery; Upwelling; Geography; Ecology; Geology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.003720039,0.0001015602,0.0003260041,0.0000975452,0.0002970072,0.0000237734,0.0003524998,0.000046724,0.02749673],"category_scores_gemma":[0.0000426401,0.0000797101,0.00009454878,0.0001870992,0.0002448581,0.0001758717,0.0002844464,0.0007307999,0.000006293368],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002306201,"about_ca_system_score_gemma":0.001332681,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9615997,"about_ca_topic_score_gemma":0.9988651,"domain_scores_codex":[0.9957027,0.0007742217,0.0009136526,0.0001456745,0.002165994,0.0002977202],"domain_scores_gemma":[0.9988733,0.0001469126,0.0003877536,0.0002254877,0.0002239528,0.0001426193],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005695176,0.0003137472,0.9412559,0.00004332487,0.0001018146,0.00003224068,0.007539,0.001430977,0.007733901,0.0001216726,0.04059554,0.000262378],"study_design_scores_gemma":[0.0004514153,0.0003391767,0.8396847,0.00001501898,0.00001446202,0.00002695156,0.0005804855,0.00001974251,0.002057508,0.0002115114,0.1565185,0.00008058271],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957897,0.000004622876,0.00006687445,0.002288003,0.0003025525,0.0001266772,0.0001117924,0.000002164917,0.001307615],"genre_scores_gemma":[0.9900663,0.00000801845,0.0001048025,0.0001457831,0.00004812664,0.000004863706,0.000035824,0.00000770316,0.009578607],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.115923,"threshold_uncertainty_score":0.9733922,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0821690255937744,"score_gpt":0.3265304205211404,"score_spread":0.244361394927366,"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."}}