{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002478872,0.0001806657,0.0002679366,0.00005120271,0.00004767832,0.000008923355,0.0002406364,0.0002054769,0.0004279268],"category_scores_gemma":[0.0000464996,0.0001375912,0.00003411783,0.0001024759,0.0005874482,0.00009569019,0.0003736526,0.0001967209,0.0004265438],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007163999,"about_ca_system_score_gemma":0.000005725189,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003068895,"about_ca_topic_score_gemma":0.000302442,"domain_scores_codex":[0.9988168,0.0001437614,0.0001608337,0.0004202738,0.0001259371,0.0003323907],"domain_scores_gemma":[0.9995173,0.0001072106,0.00007281741,0.0001747389,0.000002663886,0.0001253282],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003286154,0.0003467072,0.9570708,0.00002528359,0.00002086327,0.0001879545,0.000557559,0.002791431,0.01105905,0.0002665832,0.02680902,0.0005361816],"study_design_scores_gemma":[0.005409298,0.003758028,0.9361451,0.00005074146,0.00004656338,0.0000964659,0.0001749312,0.00786837,0.03312418,0.006304095,0.006239356,0.0007829298],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963642,0.0001309162,0.0000080148,0.0002167897,0.00008321635,0.0002049386,0.00001469212,0.0000253741,0.002951902],"genre_scores_gemma":[0.998684,0.0001060625,0.0002244317,0.0005228944,0.00001060562,0.00000975253,0.0000300131,0.000005943086,0.0004062738],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02206513,"threshold_uncertainty_score":0.5610806,"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."}}