{"id":"W2114685860","doi":"10.1111/nph.12908","title":"The context dependence of beneficiary feedback effects on benefactors in plant facilitation","year":2014,"lang":"en","type":"article","venue":"New Phytologist","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; York University","funders":"Program for New Century Excellent Talents in University; Comisión Nacional de Investigación Científica y Tecnológica; Université de Bordeaux; National Natural Science Foundation of China; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung; Agence Nationale de la Recherche; National Science Foundation","keywords":"Beneficiary; Facilitation; Context (archaeology); Productivity; Biodiversity; Scale (ratio); Psychology; Ecology; Business; Biology; Economics; Geography; Neuroscience; Economic growth","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":[0.001493592,0.0004674265,0.0005958439,0.000510996,0.0007105475,0.0008636317,0.0005224929,0.0004478165,0.003564527],"category_scores_gemma":[0.004790736,0.0003197799,0.0006332461,0.000282218,0.001292334,0.001014168,0.002000529,0.0006910576,0.0002085891],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006760387,"about_ca_system_score_gemma":0.0005891041,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004215472,"about_ca_topic_score_gemma":0.01147852,"domain_scores_codex":[0.9990857,0.0004409564,0.00005171189,0.0002155234,0.0001082444,0.00009792831],"domain_scores_gemma":[0.9960973,0.002382705,0.0005613221,0.000369679,0.0002418869,0.0003472211],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00139755,0.0003852454,0.6343642,0.001408278,0.0009057425,0.000954312,0.003115488,0.02484804,0.2600769,0.01411287,0.0004990017,0.05793246],"study_design_scores_gemma":[0.0000537957,0.0003944482,0.9629943,0.00006522441,0.0002569885,0.0003414876,0.0006255852,0.01712741,0.005643505,0.01090585,0.00151771,0.00007367734],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9917213,0.0005494689,0.004269949,0.00008996373,0.000007119483,0.00002373408,0.00007795289,0.00002305534,0.003237354],"genre_scores_gemma":[0.9989036,0.00007839294,0.0008399927,0.00002190152,0.000003841382,0.00001081312,0.00002605268,0.000005949916,0.0001094264],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004215472,"threshold_uncertainty_score":0.01192456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01096737161570627,"score_gpt":0.2312409910269917,"score_spread":0.2202736194112854,"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."}}