{"id":"W2896113399","doi":"10.1038/s41598-018-33670-x","title":"Effect of diversity on growth, mortality, and loss of resilience to extreme climate events in a tropical planted forest experiment","year":2018,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Ecosystem dynamics and resilience","field":"Environmental Science","cited_by":81,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Biodiversity; Species richness; Climate change; Ecosystem; Tropical climate; Ecology; Psychological resilience; Geography; Extreme weather; Ecosystem services; Forest dynamics; Environmental science; Environmental resource management; Agroforestry; Biology","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":[0.001177065,0.0001079602,0.0002146429,0.00008927118,0.0001690508,0.00001175054,0.0001997674,0.00004183635,0.00004821162],"category_scores_gemma":[0.0001106102,0.00008286929,0.00004025943,0.000364371,0.0005345437,0.00009120241,0.0007417655,0.00004484193,0.00001285217],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007593022,"about_ca_system_score_gemma":0.000008831781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008443028,"about_ca_topic_score_gemma":0.002142885,"domain_scores_codex":[0.9980885,0.00008505229,0.0003861926,0.0005781018,0.0006060071,0.0002561382],"domain_scores_gemma":[0.9991862,0.00004648875,0.0001973033,0.0004367508,0.00001869351,0.0001145621],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006228735,0.0000798734,0.9821024,0.00004232579,0.000002469332,0.00006474142,0.0003918174,0.0001340111,0.01697964,0.00003821385,0.00003198043,0.00007021922],"study_design_scores_gemma":[0.0001660567,0.0004833824,0.9536844,0.0001400676,0.000005904846,0.0000258099,0.00002989069,0.0009638542,0.04408366,0.0003131591,0.00001156654,0.00009223321],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981298,0.000006549243,0.00003684977,0.00001231588,0.000653532,0.0003833078,0.000004474786,0.00000673229,0.000766425],"genre_scores_gemma":[0.9998569,0.000002650285,0.00005541684,0.000005117554,0.000006831279,0.000006938853,0.000001806838,0.000003730867,0.00006063006],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02841801,"threshold_uncertainty_score":0.3379312,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01490376457725555,"score_gpt":0.264591285069171,"score_spread":0.2496875204919154,"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."}}