{"id":"W2057868137","doi":"10.1080/10659360500474623","title":"Base-line model for identifying the bioaccumulation potential of chemicals","year":2005,"lang":"en","type":"article","venue":"SAR and QSAR in environmental research","topic":"Toxic Organic Pollutants Impact","field":"Environmental Science","cited_by":120,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Bioconcentration; Bioaccumulation; Bioavailability; Chemistry; Applicability domain; Biological system; Correctness; Environmental chemistry; Predictability; Quantitative structure–activity relationship; Computer science; Biology; Mathematics; Stereochemistry; Statistics; Bioinformatics; Algorithm","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":[0.0007451291,0.00135943,0.001027834,0.0006674067,0.0002887686,0.0009059267,0.00192651,0.001252347,0.004269738],"category_scores_gemma":[0.002626329,0.0004389397,0.0009238762,0.0006012967,0.0003143696,0.001032856,0.000546571,0.001221388,0.001501998],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006446445,"about_ca_system_score_gemma":0.0006779733,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007823399,"about_ca_topic_score_gemma":0.004234661,"domain_scores_codex":[0.9997004,0.00009363867,0.00001440642,0.00007773921,0.00008062641,0.0000331113],"domain_scores_gemma":[0.9989699,0.0006793748,0.0001081782,0.00004358461,0.0001788239,0.00002014766],"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":[0.0001149955,0.00003581861,0.0007691069,0.0000565823,0.00005147084,0.00005420014,0.00001866203,0.9842556,0.002098746,0.001082822,0.0003990647,0.01106284],"study_design_scores_gemma":[0.000005869299,0.00003975552,0.0001247954,0.000002894705,0.00001160273,0.00001505273,0.000002479155,0.9982861,0.000476305,0.0007716661,0.0002594807,0.000004046475],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1145017,0.0005531666,0.8728179,0.0002357831,0.00006042478,0.0002161627,0.00172242,0.00220882,0.007683621],"genre_scores_gemma":[0.8593912,0.0005730303,0.1257293,0.0002037119,0.00005055338,0.0009801673,0.002212547,0.0002043495,0.01065525],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007823399,"threshold_uncertainty_score":0.01555574,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08589367072341933,"score_gpt":0.368534003093742,"score_spread":0.2826403323703227,"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."}}