{"id":"W2608581474","doi":"10.1111/jvs.12536","title":"Divergence between riparian seed banks and standing vegetation increases along successional trajectories","year":2017,"lang":"en","type":"article","venue":"Journal of Vegetation Science","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; Environment and Climate Change Canada; McGill University; Université Laval","funders":"Environment and Climate Change Canada; National Wildlife Research Center; Natural Sciences and Engineering Research Council of Canada; Mitacs; Ministère de l'Agriculture, des Pêcheries et de l'Alimentation","keywords":"Riparian zone; Species richness; Soil seed bank; Ecology; Ecological succession; Riparian forest; Plant community; Vegetation (pathology); Bank; Secondary succession; Geography; Habitat; Biology; Agroforestry; Seedling; Agronomy","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0003479553,0.0001108868,0.0001344383,0.0006754642,0.0003540785,0.0004868229,0.0002196952,0.0002176419,0.002374904],"category_scores_gemma":[0.001159848,0.0001058006,0.0001554204,0.0004251696,0.0003297381,0.0002074609,0.0002630043,0.0002094547,0.0002412484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005878673,"about_ca_system_score_gemma":0.0004430085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05222981,"about_ca_topic_score_gemma":0.1516666,"domain_scores_codex":[0.9998568,0.00002363413,0.000006957431,0.00005035781,0.00001811355,0.00004417002],"domain_scores_gemma":[0.9986971,0.0002412597,0.0003739179,0.00007531547,0.0002310269,0.000381314],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001357004,0.00001694082,0.9929611,0.00001231486,0.00004253332,0.00006316159,0.0002442405,0.000210967,0.003259108,0.00005321327,0.00008246141,0.002918195],"study_design_scores_gemma":[7.324963e-7,0.00000712393,0.9996518,0.000001416893,0.000001629124,0.00001230237,0.0000839816,0.0001538316,0.00003581787,0.00001388754,0.00003669861,8.130738e-7],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993533,0.00004132077,0.00009157357,0.00001273165,5.855936e-7,0.00000230255,0.0001686546,0.000003709971,0.0003257948],"genre_scores_gemma":[0.9996243,0.00001562873,0.00006667103,0.000005781781,6.263349e-7,0.000001916711,0.0001641458,0.000001117713,0.0001198985],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05222981,"threshold_uncertainty_score":0.1038516,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02205948489133387,"score_gpt":0.2981323530099265,"score_spread":0.2760728681185926,"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."}}