{"id":"W2513477796","doi":"10.1038/ncomms12573","title":"No complexity–stability relationship in empirical ecosystems","year":2016,"lang":"en","type":"article","venue":"Nature Communications","topic":"Plant and animal studies","field":"Agricultural and Biological Sciences","cited_by":178,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke; Université Laval; McGill University; Montreal Biodome; Hôpital Saint-Luc; Université du Québec à Rimouski; Health Canada","funders":"Natural Sciences and Engineering Research Council of Canada; Ministère de l'Enseignement Supérieur et de la Recherche; Ministère de l'Education Nationale, de l'Enseignement Superieur et de la Recherche; Fonds Québécois de la Recherche sur la Nature et les Technologies; Université du Québec à Rimouski","keywords":"Food web; Intuition; Stability (learning theory); Ecosystem; Ecology; Predation; Species richness; Persistence (discontinuity); Computer science; Biology; Psychology; Machine learning; Cognitive science","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":[0.0002701042,0.0000749551,0.0001169374,0.000009690356,0.0002756019,0.00001711832,0.0005594521,0.0001486104,0.0001244535],"category_scores_gemma":[0.000521131,0.00002325845,0.00004803752,0.0002628872,0.0001226558,0.00008384964,0.00021098,0.0002988485,0.000172516],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005472573,"about_ca_system_score_gemma":0.000006097841,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000114749,"about_ca_topic_score_gemma":0.08915512,"domain_scores_codex":[0.9992485,0.0001835694,0.0001806459,0.0001461319,0.00009658925,0.0001445691],"domain_scores_gemma":[0.9981934,0.001501779,0.00004755809,0.0001272117,0.00008973063,0.00004031719],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000008553346,0.0000797673,0.9772996,0.000001313626,0.00000290911,2.437943e-7,0.0000235699,8.687237e-9,0.01086731,0.007685567,0.002972534,0.001058639],"study_design_scores_gemma":[0.00006336905,0.00002027083,0.8451219,0.0000198604,0.000001766925,0.000001242455,0.00004379745,0.00001619514,0.00003923292,0.001281601,0.1533205,0.00007031704],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9531381,0.001168725,7.563355e-7,0.02721706,0.00004972387,0.0001548138,0.0001327703,0.00007174542,0.01806636],"genre_scores_gemma":[0.9992184,0.0001490125,0.0001684639,0.000172264,0.00006469782,0.00002232068,0.00003756667,4.239134e-7,0.0001668544],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.150348,"threshold_uncertainty_score":0.9274654,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.246876948867934,"score_gpt":0.3256554680218048,"score_spread":0.0787785191538708,"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."}}