{"id":"W2909763373","doi":"10.1104/pp.18.01291","title":"Engineering Plant Secondary Metabolism in Microbial Systems","year":2019,"lang":"en","type":"article","venue":"PLANT PHYSIOLOGY","topic":"Plant biochemistry and biosynthesis","field":"Biochemistry, Genetics and Molecular Biology","cited_by":174,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Plant metabolism; Secondary metabolism; Metabolism; Microbial metabolism; Biology; Biochemical engineering; Chemistry; Biochemistry; Bacteria; Engineering; Genetics; Biosynthesis; Gene","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.00009378323,0.0001877323,0.0002769302,0.00005006886,0.00001869509,0.00001161936,0.0002151625,0.0002459487,0.00005066807],"category_scores_gemma":[0.00002228819,0.0001704245,0.00006573446,0.00005278691,0.00002237378,0.000003744832,0.00008886133,0.0001529186,0.0000841517],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009708016,"about_ca_system_score_gemma":0.00004608954,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003603932,"about_ca_topic_score_gemma":0.00001065018,"domain_scores_codex":[0.9989648,0.00004303425,0.0002065105,0.0003985831,0.00005447159,0.0003326131],"domain_scores_gemma":[0.9995873,0.00003283438,0.00006093864,0.0002532467,0.00001267124,0.00005303587],"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":[0.0001805898,0.00003571501,0.000259966,0.00008003505,0.00004478805,0.000009750725,0.000008947544,0.0003174126,0.9971032,0.00006445137,0.001863931,0.00003125409],"study_design_scores_gemma":[0.000552927,0.00005077677,0.006799384,0.0000442677,0.00001085459,0.0001836366,0.00002862339,0.0004786707,0.9053834,0.00000434033,0.08614608,0.0003170593],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9972061,0.0006211258,0.000004891194,0.00002106357,0.0005304282,0.0001450869,0.0008405689,0.00001657065,0.0006141788],"genre_scores_gemma":[0.9973237,0.0001206762,0.00004711458,0.0001052809,0.0003254726,0.00001410706,0.001685481,0.00001415646,0.000364038],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09171978,"threshold_uncertainty_score":0.6949708,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003970735047403801,"score_gpt":0.1667686279289553,"score_spread":0.1627978928815515,"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."}}