{"id":"W2793215279","doi":"10.1002/etc.4124","title":"Adverse outcome pathway networks II: Network analytics","year":2018,"lang":"en","type":"article","venue":"Environmental Toxicology and Chemistry","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":149,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"Joint Research Centre; European Commission; Humane Society International; European Crop Protection Association; Society of Environmental Toxicology and Chemistry; European Chemical Industry Council; U.S. Environmental Protection Agency","keywords":"Adverse Outcome Pathway; Computer science; Directed acyclic graph; Outcome (game theory); Data science; Risk analysis (engineering); Computational biology; Business; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003835478,0.001185047,0.0007373211,0.005782798,0.0008911493,0.004204351,0.001627676,0.00107354,0.005704114],"category_scores_gemma":[0.01289671,0.0005237672,0.001293953,0.005274789,0.00104983,0.00439509,0.002592753,0.002180276,0.001099245],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002302212,"about_ca_system_score_gemma":0.001899417,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005852862,"about_ca_topic_score_gemma":0.004773258,"domain_scores_codex":[0.9982173,0.0006626968,0.0001454924,0.0004653286,0.0004139863,0.00009517118],"domain_scores_gemma":[0.9936622,0.003915491,0.0009575582,0.0006003165,0.0006450433,0.0002192459],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001604461,0.0001431112,0.01397519,0.001160637,0.0002747737,0.0005566533,0.001104836,0.4086955,0.002669469,0.3351496,0.03090243,0.2052072],"study_design_scores_gemma":[0.00001447149,0.00002868301,0.002333742,0.0001918118,0.00004419735,0.0001922421,0.0004060706,0.6001762,0.001115669,0.361584,0.03387752,0.00003544644],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01901504,0.001944288,0.9468467,0.003587925,0.0001452216,0.0005870031,0.01275734,0.002941963,0.01217446],"genre_scores_gemma":[0.31402,0.004985541,0.6493213,0.0006626961,0.0003032222,0.001473411,0.02239853,0.0004817168,0.006353658],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005852862,"threshold_uncertainty_score":0.02028424,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01282487536400891,"score_gpt":0.25041774062255,"score_spread":0.2375928652585411,"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."}}