{"id":"W4248008716","doi":"10.24908/iqurcp.8874","title":"Post-Pollution: Characterizing Ecological Recovery in a Historically Nutrient Enriched Lake.","year":2018,"lang":"en","type":"article","venue":"Inquiry Queen s Undergraduate Research Conference Proceedings","topic":"Aquatic Ecosystems and Phytoplankton Dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pollution; Algae; Nutrient; Environmental science; Nutrient pollution; Sediment; Ecology; Light pollution; Water pollution; Aquatic ecosystem; Hydrology (agriculture); Geology; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003249348,0.0001527501,0.0001718035,0.0007304327,0.0009876969,0.0008431905,0.0003602811,0.0004996503,0.0007369442],"category_scores_gemma":[0.0007497601,0.0001648005,0.0001374136,0.001297335,0.0009732308,0.0008956285,0.001034919,0.0005847408,0.0002144794],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008880452,"about_ca_system_score_gemma":0.0005177954,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02234167,"about_ca_topic_score_gemma":0.07369497,"domain_scores_codex":[0.9998767,0.00002087341,0.000007526623,0.00002203255,0.00004212595,0.0000307518],"domain_scores_gemma":[0.9997731,0.00002520162,0.0000648338,0.00001669372,0.00007379403,0.00004640463],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005326678,0.0001952826,0.8352766,0.0001846472,0.00009381114,0.001213646,0.01362558,0.001350969,0.09165736,0.001317269,0.001513498,0.05303875],"study_design_scores_gemma":[0.000001913744,0.0001106294,0.989113,0.00001018278,0.00001487002,0.0001845333,0.003645443,0.0006536318,0.003152484,0.0003044364,0.002797808,0.00001108127],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971854,0.0002998918,0.000734859,0.0001259527,0.000006417698,0.00001078314,0.0001881591,0.00001789577,0.001430505],"genre_scores_gemma":[0.9957767,0.0002890383,0.001632215,0.00009575101,0.000007374434,0.00001727445,0.0005057284,0.0000151395,0.001660838],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02234167,"threshold_uncertainty_score":0.04442322,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05048127303624322,"score_gpt":0.3110371132625125,"score_spread":0.2605558402262693,"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."}}