{"id":"W2885464363","doi":"10.1002/eco.2030","title":"Response of herbaceous wetland plant species to changing precipitation regimes","year":2018,"lang":"en","type":"article","venue":"Ecohydrology","topic":"Coastal wetland ecosystem dynamics","field":"Environmental Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"General Electric (Canada); University of Toronto","funders":"University of Toronto; Natural Sciences and Engineering Research Council of Canada; Government of Canada","keywords":"Precipitation; Herbaceous plant; Wetland; Environmental science; Evapotranspiration; Forb; Water content; Agronomy; Plant community; Biomass (ecology); Ecology; Biology; Ecological succession; Grassland; Geography; Geology","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":[0.0001772334,0.0001426662,0.000233318,0.000169213,0.0002257006,0.000231521,0.0001797626,0.000189475,0.0006600624],"category_scores_gemma":[0.000268196,0.0001424094,0.0001262308,0.0001073372,0.0001719999,0.0001357981,0.0002237342,0.0003120816,0.000082738],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000258617,"about_ca_system_score_gemma":0.0001033836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001984323,"about_ca_topic_score_gemma":0.002694894,"domain_scores_codex":[0.9999229,0.00002029603,0.000006700598,0.00002182613,0.00001207098,0.00001627535],"domain_scores_gemma":[0.9996235,0.00009223517,0.0001008976,0.0000298676,0.00004880992,0.0001045431],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0004241541,0.00010325,0.04019484,0.0000499849,0.00005018576,0.00009554458,0.00009337225,0.0003921095,0.9565729,0.00002227859,0.00004533412,0.001955893],"study_design_scores_gemma":[0.00002056957,0.0008139818,0.9671931,0.000003823225,0.00001697897,0.0001156014,0.0001735578,0.001481813,0.02970434,0.00004416711,0.0004220953,0.000009917031],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997808,0.00002042436,0.00005434847,0.000004281848,0.000001027101,0.000004362983,0.00004752906,0.000003880513,0.00008336719],"genre_scores_gemma":[0.9994494,0.00002173771,0.0001591452,0.00002690961,0.000001703156,0.00001465474,0.0001598403,0.000002640835,0.0001640384],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001984323,"threshold_uncertainty_score":0.00394547,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007613772464494217,"score_gpt":0.2105287901041381,"score_spread":0.2029150176396438,"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."}}