{"id":"W4324030820","doi":"10.1016/j.watres.2023.119875","title":"Global environmental resistome: Distinction and connectivity across diverse habitats benchmarked by metagenomic analyses","year":2023,"lang":"en","type":"article","venue":"Water Research","topic":"Pharmaceutical and Antibiotic Environmental Impacts","field":"Environmental Science","cited_by":59,"is_retracted":false,"has_abstract":false,"ca_institutions":"Agriculture and Agri-Food Canada; Western University","funders":"","keywords":"Resistome; Metagenomics; Habitat; Biology; Ecology; Microbial ecology; Antibiotic resistance; Bacteria; Genetics","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001141249,0.0001699431,0.0001680583,0.00003455572,0.0006299482,0.00009767462,0.000218946,0.00007188727,0.002266083],"category_scores_gemma":[0.00004570272,0.0001233691,0.00005734836,0.0002985975,0.001191469,0.0003100718,0.001333849,0.0002035474,0.003459418],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004359706,"about_ca_system_score_gemma":0.000002547418,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007060113,"about_ca_topic_score_gemma":0.00009543607,"domain_scores_codex":[0.9973796,0.0002977329,0.0001665548,0.000554924,0.000691437,0.0009097284],"domain_scores_gemma":[0.9993364,0.00005786012,0.00002043317,0.0002232848,0.000001839973,0.0003601343],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00008526738,0.0001530045,0.2432327,0.00001164651,0.00003285964,0.00005338856,0.0002837631,0.00006323015,0.7434855,0.00000261832,0.006953041,0.005643026],"study_design_scores_gemma":[0.00057754,0.0001178331,0.90014,0.000005956507,0.00002021255,0.00001197018,0.0005630887,0.000820405,0.08757162,0.0004861902,0.009444031,0.0002411902],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971743,0.00006019468,0.00001588381,0.0004799955,0.00005459931,0.0002299513,0.0002339952,0.00004863314,0.001702475],"genre_scores_gemma":[0.9972304,0.0001419356,0.00002392314,0.00006608901,0.00002250509,0.000008871645,0.0001147868,0.00001301751,0.002378524],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6569073,"threshold_uncertainty_score":0.998646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1250747005955237,"score_gpt":0.4257767029581007,"score_spread":0.300702002362577,"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."}}