{"id":"W4401111236","doi":"10.1016/j.ibiod.2024.105861","title":"Harnessing microbial potentials by advancing bioremediation of PAHs through molecular insights and genetics","year":2024,"lang":"en","type":"article","venue":"International Biodeterioration & Biodegradation","topic":"Microbial bioremediation and biosurfactants","field":"Environmental Science","cited_by":14,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Canada School of Energy and Environment; City University of Hong Kong","keywords":"Bioremediation; Microbial genetics; Biology; Computational biology; Biotechnology; Genetics; Biochemical engineering; Bacteria; Engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004333879,0.0005098566,0.0002580401,0.0004112427,0.0001872653,0.001433756,0.0003831089,0.0005043725,0.0009681304],"category_scores_gemma":[0.0004026506,0.0001742596,0.0003257767,0.0002405747,0.0004975667,0.001138608,0.0009054724,0.001085048,0.000312365],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005482835,"about_ca_system_score_gemma":0.0005509114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003975258,"about_ca_topic_score_gemma":0.001029275,"domain_scores_codex":[0.9998142,0.00002912004,0.00001358416,0.00002848429,0.00007244732,0.00004214843],"domain_scores_gemma":[0.999879,0.00003290468,0.0000318062,0.00001563804,0.00002101793,0.00001960121],"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":[0.00004475575,0.00008095847,0.0004420085,0.000145849,0.00001081708,0.00008750208,0.00005991604,0.00128161,0.9718058,0.007645399,0.0001626171,0.01823295],"study_design_scores_gemma":[0.00003040189,0.000430992,0.001084538,0.00006301167,0.00005005321,0.0002864964,0.0002236473,0.008537463,0.9602198,0.005251311,0.02379949,0.00002278852],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8750492,0.01080081,0.08441813,0.004919781,0.0003233962,0.0001507832,0.0004526207,0.0005734426,0.02331176],"genre_scores_gemma":[0.9479512,0.01186612,0.03651616,0.0002915776,0.00005475573,0.00006169429,0.0002710048,0.00005456463,0.002932864],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001433756,"threshold_uncertainty_score":0.003978133,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006649739319475866,"score_gpt":0.2361248693202652,"score_spread":0.2294751300007893,"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."}}