{"id":"W2810243733","doi":"10.1038/s41467-018-05056-0","title":"Identifying a common backbone of interactions underlying food webs from different ecosystems","year":2018,"lang":"en","type":"article","venue":"Nature Communications","topic":"Plant and animal studies","field":"Agricultural and Biological Sciences","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Université de Montréal; Université de Sherbrooke","funders":"Natural Sciences and Engineering Research Council of Canada; Royal Society Te Apārangi; Royal Society; Santa Fe Institute","keywords":"Ecosystem; Ecology; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001074829,0.0003187936,0.0005689318,0.001968203,0.0007235194,0.001807789,0.0006697011,0.0008666294,0.001736065],"category_scores_gemma":[0.006290528,0.0004425265,0.0005353505,0.0008332593,0.002022324,0.004249748,0.002024008,0.001045336,0.000351204],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004860802,"about_ca_system_score_gemma":0.000470318,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005808901,"about_ca_topic_score_gemma":0.0009839784,"domain_scores_codex":[0.9994519,0.0001213872,0.00004041255,0.0001955809,0.0001296713,0.0000611188],"domain_scores_gemma":[0.9956448,0.001650491,0.001196018,0.000822866,0.0003296372,0.0003562707],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004577109,0.0003797016,0.3687509,0.001101029,0.0009433308,0.001317295,0.003537643,0.04255105,0.2315674,0.216432,0.001915497,0.1310464],"study_design_scores_gemma":[0.00004804813,0.0001887738,0.2978683,0.0001375532,0.0002027358,0.001038406,0.001352868,0.1747362,0.01478959,0.5068424,0.002700466,0.00009469142],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.908318,0.0003608956,0.08625536,0.0004829502,0.00001065004,0.00004340905,0.0003505093,0.0002629704,0.003915224],"genre_scores_gemma":[0.9757717,0.0001750978,0.02335217,0.00006141204,0.00001396935,0.00003705671,0.0003397108,0.00003999142,0.0002087978],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001968203,"threshold_uncertainty_score":0.005807757,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1678357439499335,"score_gpt":0.3233524929169171,"score_spread":0.1555167489669836,"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."}}