{"id":"W3036705770","doi":"10.1016/j.jhazmat.2020.123245","title":"New equation to predict size-resolved gas-particle partitioning quotients for polybrominated diphenyl ethers","year":2020,"lang":"en","type":"article","venue":"Journal of Hazardous Materials","topic":"Toxic Organic Pollutants Impact","field":"Environmental Science","cited_by":50,"is_retracted":false,"has_abstract":false,"ca_institutions":"Fisheries and Oceans Canada","funders":"Harbin Institute of Technology; State Key Laboratory of Urban Water Resource and Environment; National Natural Science Foundation of China","keywords":"Polybrominated diphenyl ethers; Quotient; Particle size; Particulates; Environmental chemistry; Chemistry; Partition (number theory); Partition coefficient; Mathematics; Pollutant; Organic chemistry; Physical chemistry","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":[0.000501706,0.0007136046,0.0006863104,0.0005091495,0.0003254833,0.0004134125,0.0009818143,0.001058743,0.001022408],"category_scores_gemma":[0.001361701,0.000367958,0.0006706748,0.0003344695,0.000214675,0.00132324,0.0004109665,0.0009210228,0.000852828],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008050405,"about_ca_system_score_gemma":0.0007410566,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008236566,"about_ca_topic_score_gemma":0.007372651,"domain_scores_codex":[0.999743,0.00003053501,0.0000166531,0.0000701902,0.0001193612,0.00002013018],"domain_scores_gemma":[0.9996595,0.0001253655,0.00002194821,0.00002683599,0.0001584467,0.000007789049],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000145573,0.0003348037,0.01617821,0.0004931201,0.0002682717,0.0004305683,0.0002357193,0.5521631,0.2123007,0.02066179,0.008373181,0.1884151],"study_design_scores_gemma":[0.00001111299,0.00002430141,0.001329951,0.000005935402,0.00003134481,0.00003921018,0.00001044688,0.9806889,0.01457852,0.0009360934,0.002329265,0.00001495636],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05729618,0.0008130419,0.9375436,0.0001964854,0.0003063609,0.0001467963,0.000479908,0.001195168,0.002022422],"genre_scores_gemma":[0.6855176,0.001790873,0.290978,0.0003113829,0.0001401683,0.0006506149,0.001396568,0.0003573112,0.01885744],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008236566,"threshold_uncertainty_score":0.01637721,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02246295254912382,"score_gpt":0.2516309575839789,"score_spread":0.2291680050348551,"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."}}