{"id":"W3088835683","doi":"10.1002/ecy.3205","title":"Co‐occurrence history increases ecosystem stability and resilience in experimental plant communities","year":2020,"lang":"en","type":"article","venue":"Ecology","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; McGill University","funders":"Deutsche Forschungsgemeinschaft","keywords":"Ecological stability; Ecosystem; Biodiversity; Ecology; Biomass (ecology); Abiotic component; Plant community; Species richness; Disturbance (geology); Environmental science; Psychological resilience; Grassland; Context (archaeology); Flooding (psychology); Ecosystem diversity; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001850915,0.00008253507,0.0001590094,0.00001705314,0.0001068872,0.000003052328,0.0001335637,0.00005204203,0.00157715],"category_scores_gemma":[0.00006405656,0.00008379868,0.00001216048,0.00004057044,0.0004822082,0.00009930729,0.0001558698,0.0001251729,0.00008948819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002816455,"about_ca_system_score_gemma":0.00001703995,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002809186,"about_ca_topic_score_gemma":0.01930661,"domain_scores_codex":[0.9992159,0.0002264957,0.0001664873,0.0001755884,0.00005396712,0.000161544],"domain_scores_gemma":[0.9994978,0.0002989912,0.00005366816,0.00008901535,0.000002996516,0.00005752638],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003043101,0.00008242967,0.9913623,0.000011157,0.000003011416,0.000009270823,0.006594174,0.00007964673,0.000461345,0.0001624486,0.001185813,0.00001800327],"study_design_scores_gemma":[0.0003968642,0.0002849626,0.9840587,0.000004344216,0.000003460546,0.00001091035,0.007594707,0.004902526,0.0004265692,0.00005614516,0.002115258,0.0001454984],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966423,0.0002240488,0.000005299386,0.0002681021,0.00008012324,0.000133933,0.0000408368,0.00002222566,0.00258316],"genre_scores_gemma":[0.9991742,0.00004058037,0.00005114855,0.0006562585,0.000005759728,0.00004064789,0.00001804257,0.000002314545,0.00001107846],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01902569,"threshold_uncertainty_score":0.9993355,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02597026672999914,"score_gpt":0.2395613614391482,"score_spread":0.2135910947091491,"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."}}