{"id":"W6921792249","doi":"10.1021/acs.est.4c03695.s001","title":"Assessment\\nof Global\\nAntibiotic Exposure Risk for\\nCrops: Incorporating Soil Adsorption via Machine Learning","year":2024,"lang":"en","type":"article","venue":"Figshare","topic":"Education Methods and Technologies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Agriculture; Risk assessment; Crop; Moisture; Soil water","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006131523,0.0001161007,0.000128608,0.0000651048,0.0005403783,0.0003140975,0.000223942,0.0001735095,0.008353736],"category_scores_gemma":[0.003517752,0.0001080518,0.00009038299,0.0005403394,0.00002737112,0.0002570476,0.00006939169,0.0002992841,0.0002043572],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001649163,"about_ca_system_score_gemma":0.0002790298,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000356544,"about_ca_topic_score_gemma":0.0007449366,"domain_scores_codex":[0.998819,0.00023335,0.0001892838,0.0002872476,0.0002251898,0.0002459179],"domain_scores_gemma":[0.9991859,0.0003451321,0.0001510401,0.0001395037,0.0001319707,0.0000464255],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000008819074,0.0001244221,0.09484152,0.001153997,0.0001436019,0.00001608388,0.004048706,0.0004605485,0.001330812,0.03542697,0.0977722,0.7646723],"study_design_scores_gemma":[0.0004840672,0.0004064597,0.03374702,0.003673389,0.0001191422,0.000007869399,0.01364176,0.02407184,0.001163964,0.06686791,0.8547763,0.001040254],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.252986,0.04045309,0.05375579,0.02183864,0.00967908,0.008578149,0.3866152,0.02271892,0.2033751],"genre_scores_gemma":[0.9760892,0.0000443163,0.01511858,0.00004306223,0.0003360871,0.00008210412,0.007564394,0.0000177307,0.0007045212],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7636321,"threshold_uncertainty_score":0.9925528,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05079752235270407,"score_gpt":0.3879030799098896,"score_spread":0.3371055575571856,"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."}}