{"id":"W2793019704","doi":"10.1002/etc.4125","title":"Adverse outcome pathway networks I: Development and applications","year":2018,"lang":"en","type":"article","venue":"Environmental Toxicology and Chemistry","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":235,"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; Context (archaeology); Computer science; Aspect-oriented programming; Outcome (game theory); Stakeholder; Set (abstract data type); Software engineering; Data science; Programming language; Software; Computational biology; 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":[0.006880202,0.001223009,0.000514189,0.00385769,0.001084301,0.004533465,0.001696406,0.001379627,0.00703267],"category_scores_gemma":[0.0180768,0.0006573877,0.001191514,0.003635185,0.001407042,0.004904721,0.003343249,0.001889562,0.001145869],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004495015,"about_ca_system_score_gemma":0.002649021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007381499,"about_ca_topic_score_gemma":0.0057726,"domain_scores_codex":[0.9975148,0.00101832,0.00017319,0.0004504561,0.0007245736,0.0001187177],"domain_scores_gemma":[0.9906846,0.005469556,0.001009637,0.0008120579,0.001726811,0.000297375],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001015541,0.0001299909,0.007018476,0.0009009044,0.0001118897,0.0004427065,0.001095112,0.1428275,0.002858927,0.50615,0.01725625,0.3211068],"study_design_scores_gemma":[0.00002178607,0.0001140982,0.002570437,0.0007759972,0.00007136916,0.000461611,0.0008752263,0.4566787,0.004729548,0.3756427,0.1579639,0.00009459316],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01002127,0.001937287,0.9461672,0.003752711,0.0002123646,0.0005818832,0.001843906,0.001587988,0.03389536],"genre_scores_gemma":[0.1414142,0.007405604,0.8373048,0.0005048076,0.0002486828,0.001077773,0.002464647,0.0003730628,0.009206605],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007381499,"threshold_uncertainty_score":0.03638643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01127986443004717,"score_gpt":0.2460256742919014,"score_spread":0.2347458098618543,"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."}}