{"id":"W4293153990","doi":"10.1002/etc.5462","title":"The Path to UVCB Ecological Risk Assessment: Grappling with Substance Characterization","year":2022,"lang":"en","type":"article","venue":"Environmental Toxicology and Chemistry","topic":"Animal testing and alternatives","field":"Veterinary","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Risk assessment; Risk analysis (engineering); Hazard; Hazard analysis; Process (computing); Computer science; Characterization (materials science); Environmental resource management; Environmental planning; Environmental science; Ecology; Business; Engineering; Biology; Reliability engineering; Nanotechnology; Computer security","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.02985477,0.001597613,0.002074403,0.0039226,0.0026711,0.01244699,0.003685639,0.003792603,0.0030188],"category_scores_gemma":[0.01572159,0.001021908,0.001507703,0.00216544,0.009221291,0.009026424,0.006908525,0.008015557,0.001215161],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01058321,"about_ca_system_score_gemma":0.02787025,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03808403,"about_ca_topic_score_gemma":0.06192124,"domain_scores_codex":[0.9844413,0.00487624,0.000739679,0.001452472,0.007864151,0.0006260572],"domain_scores_gemma":[0.9796323,0.005792494,0.001694487,0.002591666,0.009226546,0.001062455],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004290028,0.0005296335,0.0393261,0.002934849,0.0004134325,0.001040855,0.003168297,0.02786266,0.08109604,0.1424091,0.02909943,0.6716906],"study_design_scores_gemma":[0.00004394243,0.001281267,0.02427925,0.001940928,0.0002859436,0.002136271,0.007869444,0.03675359,0.08702055,0.395211,0.4426243,0.000553546],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06027876,0.06278931,0.7444666,0.09081452,0.001533391,0.001299643,0.001537626,0.001316419,0.03596373],"genre_scores_gemma":[0.1827049,0.03947607,0.7487216,0.01221153,0.0006046236,0.0005223343,0.0007932007,0.0004148742,0.01455096],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03808403,"threshold_uncertainty_score":0.157889,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02550178984878639,"score_gpt":0.2873064426048323,"score_spread":0.2618046527560459,"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."}}