{"id":"W2537476455","doi":"10.1186/s40538-016-0080-6","title":"An effective bioremediation approach for enhanced microbial degradation of the veterinary antibiotic sulfamethazine in an agricultural soil","year":2016,"lang":"en","type":"article","venue":"Chemical and Biological Technologies in Agriculture","topic":"Pharmaceutical and Antibiotic Environmental Impacts","field":"Environmental Science","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Mineralization (soil science); Bioremediation; Bioaugmentation; Microbial population biology; Chemistry; Environmental chemistry; Biodegradation; Soil contamination; Soil water; Contamination; Environmental science; Bacteria; Biology; Ecology; Soil science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001253572,0.0001558853,0.0001908276,0.00001595918,0.00003646893,0.000008159165,0.0002931646,0.0003142326,0.000005703991],"category_scores_gemma":[0.000165619,0.00005567423,0.00004471578,0.0002583881,0.0006768234,0.0001930614,0.0002499799,0.000148513,0.00000115249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008687111,"about_ca_system_score_gemma":0.000001042832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005923433,"about_ca_topic_score_gemma":0.000005746298,"domain_scores_codex":[0.9990383,0.00006015204,0.0001917729,0.0003702082,0.00008124342,0.0002583079],"domain_scores_gemma":[0.9996857,0.00008149096,0.00007262836,0.0001156644,0.000005037312,0.00003947556],"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":[0.00005069575,0.0003167717,0.03203595,0.00001071881,0.000001942118,3.724045e-7,0.00001518826,0.000009405879,0.9345042,0.00002743911,0.0000105597,0.03301677],"study_design_scores_gemma":[0.000381391,0.0002497005,0.3051012,0.00002366486,0.000003212808,0.000003458204,0.0001412924,0.00002484465,0.6937007,0.0002594528,0.000009402739,0.0001017139],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988322,0.00003088341,0.0001324168,0.000342015,0.0000248248,0.0005088353,0.0000217789,0.00005075347,0.00005624883],"genre_scores_gemma":[0.998383,0.00009102374,0.001420805,0.00002998377,0.00001522808,0.00001861759,0.00003078552,0.000002686821,0.000007865389],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2730652,"threshold_uncertainty_score":0.2493784,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01927387865820445,"score_gpt":0.2537611620552182,"score_spread":0.2344872833970137,"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."}}