{"id":"W2203831776","doi":"10.1007/s10750-015-2531-7","title":"Effects of hydrological regime, landscape features, and environment on macroinvertebrates in St. Lawrence River wetlands","year":2015,"lang":"en","type":"article","venue":"Hydrobiologia","topic":"Freshwater macroinvertebrate diversity and ecology","field":"Environmental Science","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"Environment and Climate Change Canada; Université de Montréal; Université du Québec à Montréal","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Chironomidae; Ecology; Wetland; Invertebrate; Malacostraca; Species richness; Oligochaeta (plant); Vegetation (pathology); Water level; Abundance (ecology); Environmental science; Biology; Geography; Crustacean; Decapoda","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":[0.0003488924,0.0001125613,0.0001983963,0.0004070837,0.0005437883,0.0006025324,0.0002991585,0.0002257276,0.000933132],"category_scores_gemma":[0.0006976527,0.0002004038,0.0002470131,0.0003842034,0.000724898,0.000343511,0.0005946579,0.0002165693,0.0001096716],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001451534,"about_ca_system_score_gemma":0.00100501,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1612327,"about_ca_topic_score_gemma":0.558516,"domain_scores_codex":[0.9996964,0.0001014838,0.00002257555,0.00004763254,0.00003749215,0.00009452998],"domain_scores_gemma":[0.9992971,0.0001483132,0.0001727757,0.00003340458,0.0001086363,0.0002397733],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002428673,0.0001218981,0.9928125,0.00001325355,0.00008619297,0.0001140195,0.0003095175,0.0004088733,0.002176761,0.00006736128,0.0002165831,0.003430209],"study_design_scores_gemma":[0.000002219363,0.00002602645,0.9995131,0.000001557983,0.000006307719,0.00001365498,0.0001913941,0.0001430088,0.00004109507,0.000009829716,0.00004981071,0.000001994415],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9998025,0.00001481496,0.000008366197,0.00001313801,6.496754e-7,7.253863e-7,0.00003086242,0.000001075191,0.000127925],"genre_scores_gemma":[0.9997404,0.00001584604,0.0000183242,0.00001020709,0.000001093826,0.000001644824,0.00005764006,8.160279e-7,0.0001541099],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8387673,"threshold_uncertainty_score":0.3205885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00878468853924124,"score_gpt":0.1815632442388512,"score_spread":0.17277855569961,"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."}}