{"id":"W4404886083","doi":"","title":"Using macroinvertebrate functional traits for assessing sediment quality in the St. Lawrence River","year":2010,"lang":"en","type":"preprint","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Freshwater macroinvertebrate diversity and ecology","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Ministère des Ressources naturelles et des Forêts","funders":"","keywords":"Sediment; Environmental science; Hydrology (agriculture); Quality (philosophy); Water quality; Geology; Ecology; Geotechnical engineering; Geomorphology; Biology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0004031159,0.000232913,0.0001794534,0.001113209,0.0003829614,0.0006518721,0.0002368127,0.0002335991,0.0003244547],"category_scores_gemma":[0.0008132286,0.0001567613,0.000146378,0.0009080297,0.000371229,0.0003236518,0.0003589742,0.0001516184,0.00008868206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005836522,"about_ca_system_score_gemma":0.0004739786,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0661926,"about_ca_topic_score_gemma":0.2929317,"domain_scores_codex":[0.9997371,0.00007658359,0.00002367865,0.00006195336,0.0000596553,0.00004093048],"domain_scores_gemma":[0.999451,0.000103439,0.0002115299,0.00003817294,0.0001172298,0.00007874206],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004014051,0.00001723836,0.9904413,0.0000136783,0.0000351268,0.00002770783,0.0002299097,0.0001364117,0.004246601,0.00001318229,0.00002587483,0.004772859],"study_design_scores_gemma":[8.674128e-7,0.00002698416,0.999338,0.000001779183,0.000003907866,0.00001856541,0.0001274919,0.0002261853,0.000205295,0.000006862721,0.0000419128,0.000002211242],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995758,0.00003181178,0.0001663787,0.000006363728,2.89329e-7,0.000002735168,0.00007558026,0.000002667058,0.00013834],"genre_scores_gemma":[0.9990471,0.00003764602,0.0006374706,0.000005145805,8.670569e-7,0.000005379366,0.0001464399,0.000001015669,0.0001189763],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9338074,"threshold_uncertainty_score":0.1316146,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04473182318566323,"score_gpt":0.2610369694446668,"score_spread":0.2163051462590036,"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."}}