{"id":"W1990608807","doi":"10.1016/j.mimet.2004.04.015","title":"Identification and quantification of arsC genes in environmental samples by using real-time PCR","year":2004,"lang":"en","type":"article","venue":"Journal of Microbiological Methods","topic":"Arsenic contamination and mitigation","field":"Environmental Science","cited_by":135,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"","keywords":"Arsenic; Arsenate; Biology; Gene; SYBR Green I; Real-time polymerase chain reaction; Molecular biology; Genetics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001286528,0.00007281487,0.000171689,0.00004781374,0.00003614678,0.000008587264,0.00009458106,0.00007902726,0.0001731069],"category_scores_gemma":[0.0000988467,0.00005798683,0.00004469663,0.00008506209,0.0001847099,0.0001377922,0.0000430342,0.00007856287,0.000005549517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001512692,"about_ca_system_score_gemma":0.000007501649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003921683,"about_ca_topic_score_gemma":0.000003017244,"domain_scores_codex":[0.9989199,0.000282402,0.0005009438,0.0001329402,0.0000768363,0.00008696787],"domain_scores_gemma":[0.9993186,0.0001136945,0.0004510733,0.00007141316,0.000007542003,0.00003765901],"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":[0.00001512157,0.0000780612,0.005296636,0.00000194506,0.00000399503,5.859371e-7,0.0001186626,0.0003010755,0.9523104,0.00002684117,0.00001363297,0.04183302],"study_design_scores_gemma":[0.0005194863,0.000106722,0.1639616,0.00002245423,0.00002056852,0.0000683078,0.0002112595,0.0002793313,0.8329467,0.001100403,0.000660479,0.0001025998],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9413188,0.000195583,0.05821664,0.0001079054,0.00003912284,0.0000824942,0.000008475564,0.000002757145,0.000028231],"genre_scores_gemma":[0.89555,0.0004582939,0.103916,0.00001978564,0.000008845473,7.376793e-7,0.000006939442,0.000003534353,0.00003586195],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.158665,"threshold_uncertainty_score":0.2364634,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03905131453751126,"score_gpt":0.3220440387419864,"score_spread":0.2829927242044752,"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."}}