{"id":"W2127323319","doi":"10.1002/iroh.200610877","title":"Effect of Seasonal Changes on Predictive Model Assessments of Streams Water Quality with Macroinvertebrates","year":2006,"lang":"en","type":"article","venue":"International Review of Hydrobiology","topic":"Freshwater macroinvertebrate diversity and ecology","field":"Environmental Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Acadia University; Environment and Climate Change Canada","funders":"Universidade de Coimbra; Acadia University","keywords":"Invertebrate; STREAMS; Seasonality; Environmental science; Ecology; Taxonomic rank; Water quality; Drainage basin; Biology; Geography; Taxon","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.004847942,0.000586667,0.0005491339,0.000268564,0.0002964123,0.00108135,0.0005741382,0.0004671748,0.0005528516],"category_scores_gemma":[0.01394425,0.0003328771,0.0005947049,0.0002228853,0.0005052302,0.0008247442,0.0007920258,0.0007667515,0.00008809737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005774295,"about_ca_system_score_gemma":0.0005485691,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009984493,"about_ca_topic_score_gemma":0.007125624,"domain_scores_codex":[0.998598,0.0007693534,0.00009493611,0.0002186799,0.0002100216,0.0001090565],"domain_scores_gemma":[0.9900034,0.007591386,0.000899745,0.0006387569,0.0006580356,0.0002085931],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0007209975,0.0001728364,0.1492426,0.00005125259,0.0003713735,0.00009758747,0.00009890678,0.8230671,0.003663457,0.0002429574,0.0002007598,0.02207015],"study_design_scores_gemma":[0.00001441263,0.0002347774,0.02093062,0.000009606715,0.0000512459,0.00002933575,0.00004359632,0.9765733,0.001784712,0.0002398067,0.00007738978,0.00001116113],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9798654,0.0001483787,0.01901768,0.0001059927,0.00001606818,0.00001923452,0.00008674107,0.0001637998,0.0005765414],"genre_scores_gemma":[0.9980547,0.00002950854,0.001702183,0.00001576714,0.00000320948,0.000007609844,0.00008029887,0.000009897395,0.00009674509],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009984493,"threshold_uncertainty_score":0.0256387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007509904144060727,"score_gpt":0.270184583626517,"score_spread":0.2626746794824563,"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."}}