{"id":"W2075866734","doi":"10.1080/07438140903117688","title":"Assessing hypolimnetic oxygen concentrations in Canadian Shield lakes: Deriving management benchmarks using two methods","year":2009,"lang":"en","type":"article","venue":"Lake and Reservoir Management","topic":"Marine and coastal ecosystems","field":"Earth and Planetary Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; Queen's University; Ministry of the Environment, Conservation and Parks","funders":"Natural Sciences and Engineering Research Council of Canada; Ministry of Natural Resources","keywords":"Hypolimnion; Environmental science; Paleolimnology; Shore; Climate change; Ecology; Hydrology (agriculture); Eutrophication; Oceanography; Geology; Biology; Nutrient","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":[0.001654717,0.0009534459,0.0003566244,0.001522462,0.0009399331,0.001424039,0.001114102,0.0006722702,0.0004661433],"category_scores_gemma":[0.004981887,0.0002601591,0.0004853392,0.001164132,0.0004234548,0.000576885,0.0008140749,0.0003679465,0.00007257787],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01123291,"about_ca_system_score_gemma":0.009356942,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8399407,"about_ca_topic_score_gemma":0.8632739,"domain_scores_codex":[0.99918,0.0001459019,0.00003848876,0.0001490528,0.0003885311,0.00009800932],"domain_scores_gemma":[0.9984235,0.000430895,0.0002581662,0.00006849822,0.0007145065,0.0001045172],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002854925,0.0002038563,0.5366182,0.0001585415,0.0003244385,0.00008523676,0.0004112626,0.4137482,0.003776604,0.001310256,0.001224925,0.0418531],"study_design_scores_gemma":[0.00003370814,0.00007935306,0.2447301,0.00003525814,0.0000455888,0.00002168333,0.0003409831,0.7505436,0.002435409,0.0005800157,0.001102028,0.00005223513],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9802278,0.000345806,0.01362941,0.0002518114,0.00001077641,0.0001077416,0.001576202,0.0002047678,0.003645704],"genre_scores_gemma":[0.9904455,0.0001034063,0.007866757,0.00003439097,0.000003666999,0.00006337484,0.001073244,0.00001094455,0.0003985873],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1600593,"threshold_uncertainty_score":0.3220037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02500146356877133,"score_gpt":0.2952001071699492,"score_spread":0.2701986436011779,"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."}}