{"id":"W6930331234","doi":"10.5281/zenodo.1346276","title":"EcologicalNetworks.jl - analysing ecological networks of species interactions","year":2019,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Optimization Algorithms Research","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Ecological network; Measure (data warehouse); Ecological systems theory; Nestedness; Natural (archaeology); R package","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":["insufficient_payload"],"category_scores_codex":[0.0008252269,0.00015555,0.0003049449,0.0002761518,0.0009108349,0.0002761328,0.000808742,0.00009892743,0.05058962],"category_scores_gemma":[0.001639684,0.0001450931,0.0001073666,0.0009665933,0.0002098754,0.0002772108,0.001069889,0.0004748233,0.001640625],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002018763,"about_ca_system_score_gemma":0.000004023472,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001526584,"about_ca_topic_score_gemma":6.206248e-7,"domain_scores_codex":[0.997849,0.0004621676,0.0004510633,0.0004005447,0.0004085178,0.0004286908],"domain_scores_gemma":[0.9979957,0.0003317909,0.0002351068,0.0005053306,0.0007849723,0.0001471441],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006535525,0.003615593,0.0004556626,0.0004656122,0.0008395607,0.00007650923,0.001982065,0.3128612,0.008593176,0.223766,0.2994888,0.1472023],"study_design_scores_gemma":[0.001139788,0.0006188645,0.003630873,0.00007967478,0.00005261645,0.00009808881,0.0010178,0.1997893,0.0002932134,0.006189333,0.7866356,0.0004548341],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08211353,0.00008892959,0.6033014,0.00103282,0.0004226863,0.001813571,0.0001266651,0.001551505,0.3095489],"genre_scores_gemma":[0.9733683,0.0001159768,0.01845953,0.000078524,0.0002001045,1.325641e-7,0.0005924588,0.0008663188,0.006318609],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8912548,"threshold_uncertainty_score":0.9991367,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07219712731602704,"score_gpt":0.3138307110810045,"score_spread":0.2416335837649774,"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."}}