{"id":"W4366492316","doi":"10.11159/iceptp23.123","title":"Phytoextraction of Dieldrin from a Historically Contaminated: Focus On Accumulation and Distribution in Various Plant Species","year":2023,"lang":"en","type":"article","venue":"Proceedings of the World Congress on Civil, Structural, and Environmental Engineering","topic":"Biochemical and biochemical processes","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Phytoremediation; Dieldrin; Contamination; Environmental science; Environmental chemistry; Distribution (mathematics); Focus (optics); Heavy metals; Waste management; Chemistry; Agronomy; Biology; Pesticide; Engineering; Ecology; Mathematics; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003261819,0.0001196518,0.0001267966,0.00003511223,0.00002776836,0.000009059018,0.00007848982,0.00007155821,0.000003269949],"category_scores_gemma":[0.0000348108,0.00009121115,0.00002904323,0.00008425975,0.00006933332,0.000009437115,0.00008287151,0.00009948285,1.666008e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002903647,"about_ca_system_score_gemma":0.000001834908,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000198162,"about_ca_topic_score_gemma":0.00001242533,"domain_scores_codex":[0.9994289,0.000002123449,0.0001544305,0.0001981893,0.000107721,0.0001086948],"domain_scores_gemma":[0.9998049,0.00002496517,0.00008366038,0.00004924564,0.00000664281,0.00003055392],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001235828,0.0000161602,0.007540667,0.00005592506,0.00001607034,2.696403e-7,0.00002174999,0.0001088695,0.9909733,0.0001579483,0.0001295683,0.0008558944],"study_design_scores_gemma":[0.0003057339,0.00008009361,0.1274026,0.00009979946,0.00001113513,0.000001812173,0.00002923316,0.001778167,0.8694856,0.0002985225,0.000394507,0.000112742],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9993644,0.0001787669,0.000005287614,0.00009407489,0.00009480481,0.00009073198,0.0001098066,0.000008353738,0.00005374983],"genre_scores_gemma":[0.9995279,0.0002148845,0.00002414409,0.00001052186,0.00003702012,0.000005963122,0.00009305536,0.000007700017,0.00007877564],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1214877,"threshold_uncertainty_score":0.3719483,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007107018134715902,"score_gpt":0.1945658103536188,"score_spread":0.1874587922189029,"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."}}