{"id":"W4389016630","doi":"10.1096/fasebj.31.1_supplement.924.4","title":"Genome‐Wide Screen for <i>Escherichia coli</i> [NiFe]‐Hydrogenase Maturation Factors","year":2017,"lang":"en","type":"article","venue":"The FASEB Journal","topic":"Metalloenzymes and iron-sulfur proteins","field":"Energy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; University of Toronto","funders":"Canadian Institutes of Health Research","keywords":"Hydrogenase; Archaea; Function (biology); Escherichia coli; Bimetallic strip; Chemistry; Computational biology; Bacteria; Gene; Biology; Enzyme; Biochemistry; Combinatorial chemistry; Catalysis; Cell biology; Genetics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.0007130346,0.0005968639,0.0008487493,0.000827934,0.0004637223,0.0007540172,0.0006761798,0.0007096159,0.0009529187],"category_scores_gemma":[0.000669636,0.0002243926,0.0005362432,0.001018223,0.0002396051,0.0001644956,0.0004381959,0.0004571577,0.0004602614],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005156477,"about_ca_system_score_gemma":0.0009175485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00474372,"about_ca_topic_score_gemma":0.01004753,"domain_scores_codex":[0.9993729,0.00008265101,0.00004721467,0.0001921355,0.0002234015,0.00008176082],"domain_scores_gemma":[0.9996036,0.0001074197,0.00007086742,0.00003412161,0.0000985541,0.0000854301],"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":[0.0002836731,0.0001570228,0.01516451,0.0002288085,0.0001397927,0.0003335458,0.00005043483,0.0002762398,0.9757209,0.00005744977,0.001255292,0.00633237],"study_design_scores_gemma":[0.0001790843,0.001477404,0.3560389,0.0000647698,0.0008677876,0.002725268,0.0003438831,0.003410205,0.6014345,0.0001270877,0.03323635,0.00009472905],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9519364,0.004921701,0.01039726,0.0007187295,0.00007690597,0.0005106492,0.02738008,0.0008216791,0.003236513],"genre_scores_gemma":[0.9197553,0.002776946,0.02716784,0.001173083,0.00004883348,0.0002118591,0.04586547,0.0001591828,0.002841491],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00474372,"threshold_uncertainty_score":0.009432256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02989035325763774,"score_gpt":0.2520604582867864,"score_spread":0.2221701050291487,"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."}}