{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001197816,0.0000926421,0.0001085359,0.00005385641,0.0001329089,0.00001812137,0.0002232001,0.0000682577,0.0006524956],"category_scores_gemma":[0.00008135034,0.00007061608,0.00004020428,0.0001282086,0.0004979561,0.0001974828,0.000276481,0.0001855815,0.00005784862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002380296,"about_ca_system_score_gemma":0.000008558462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003495139,"about_ca_topic_score_gemma":0.00003140273,"domain_scores_codex":[0.9985434,0.00007259959,0.0002329696,0.0002579317,0.0005269382,0.0003661392],"domain_scores_gemma":[0.999532,0.0001248514,0.00004062005,0.000222749,6.774904e-7,0.00007906221],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00007212405,0.000148533,0.003015564,0.000005766026,0.000006180423,8.74698e-7,0.0005393961,0.005801431,0.8947672,0.0000127209,0.0001122631,0.09551792],"study_design_scores_gemma":[0.001018589,0.00008461718,0.0953005,0.00001566462,0.000009954281,0.000007509901,0.000440084,0.6990105,0.2009853,0.002543064,0.0004219574,0.0001622684],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965639,0.0002096794,0.001782349,0.0006692047,0.00001558135,0.000412325,0.00009952167,0.000005591009,0.0002418807],"genre_scores_gemma":[0.9975232,0.0001535736,0.001748322,0.00005451457,0.00004287305,0.000006948828,0.000004191932,0.0000158457,0.0004505334],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6937819,"threshold_uncertainty_score":0.7144369,"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."}}