{"id":"W4234786236","doi":"10.21203/rs.3.rs-91181/v1","title":"Engineering Escherichia Coli for the Utilization of Ethylene Glycol","year":2020,"lang":"en","type":"preprint","venue":"Research Square","topic":"CO2 Reduction Techniques and Catalysts","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Ethylene glycol; Escherichia coli; Chemistry; Biochemistry; Organic 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001860142,0.0004252981,0.0001618443,0.0001764251,0.00009206752,0.0004015702,0.0002537324,0.0003264837,0.0003426823],"category_scores_gemma":[0.0001809622,0.0001223796,0.0002533821,0.0003599699,0.0001043155,0.0001614797,0.0003040837,0.0004777553,0.0003369488],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003408496,"about_ca_system_score_gemma":0.0003320492,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001705501,"about_ca_topic_score_gemma":0.001925525,"domain_scores_codex":[0.9998187,0.00003354531,0.00002262927,0.00002895465,0.00005755136,0.00003862128],"domain_scores_gemma":[0.9998999,0.0000252091,0.00003322144,0.00001045165,0.00002087717,0.00001036938],"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":[0.00005217028,0.0001532142,0.001077684,0.00005290277,0.000008824219,0.00009829002,0.00001674069,0.0005767016,0.9954373,0.0001397191,0.00004908382,0.002337412],"study_design_scores_gemma":[0.00001204776,0.0003152972,0.002956989,0.00001194324,0.00002212902,0.0002276415,0.00005968487,0.004272908,0.9896445,0.00005437884,0.002415743,0.000006734261],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9852275,0.0003482397,0.01195244,0.0002326831,0.00003264803,0.00006977239,0.0004024637,0.0001052214,0.001629067],"genre_scores_gemma":[0.974872,0.000545537,0.02078016,0.0001022833,0.000004784819,0.00003453807,0.0009658611,0.00003051289,0.002664265],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001705501,"threshold_uncertainty_score":0.003391206,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1148197726312507,"score_gpt":0.3937538774036565,"score_spread":0.2789341047724058,"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."}}