{"id":"W4394131714","doi":"10.6084/m9.figshare.21393562","title":"Additional file 1 of Deciphering chloramphenicol biotransformation mechanisms and microbial interactions via integrated multi-omics and cultivation-dependent approaches","year":2022,"lang":"en","type":"dataset","venue":"Open MIND","topic":"Steroid Chemistry and Biochemistry","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Biotransformation; Chloramphenicol; Computational biology; Biology; Omics; Biotechnology; Microbiology; Biochemical engineering; Bioinformatics; Engineering; Antibiotics; Biochemistry","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":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00007092999,0.0002378241,0.0002082839,0.00002786408,0.0001313062,0.00008839096,0.0002905673,0.0002619375,0.3796631],"category_scores_gemma":[0.00008956649,0.0002481504,0.0000642114,0.00006185444,0.00007370295,0.00001534521,0.0004332127,0.0002361587,0.000004651392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003205342,"about_ca_system_score_gemma":0.000119718,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002459161,"about_ca_topic_score_gemma":0.00006390502,"domain_scores_codex":[0.9989882,0.00002544246,0.0003150251,0.0004358321,0.0001040914,0.0001313761],"domain_scores_gemma":[0.9993194,0.00005773437,0.0002656393,0.0002400976,0.00005475563,0.0000623443],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000809786,0.0001016703,1.790797e-7,0.00005572939,0.00009839066,8.472741e-7,0.00002298076,0.000005628854,0.2321499,2.528595e-8,0.765,0.002483662],"study_design_scores_gemma":[0.0003405017,0.00004567492,0.000002127002,0.00006399477,0.00003523305,0.00006220487,0.000255259,0.00009461357,0.2814815,0.000001577365,0.717413,0.0002042987],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001986724,0.00002440564,0.0003328878,0.000009816023,0.00004826892,0.0002983125,0.997253,8.671399e-7,0.00004573891],"genre_scores_gemma":[0.0002117921,0.00004341182,0.009766331,0.00001922458,0.00005882148,0.0002405702,0.9891558,0.00001317404,0.0004908487],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3796584,"threshold_uncertainty_score":0.9999971,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02912711486307693,"score_gpt":0.2546708107300375,"score_spread":0.2255436958669606,"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."}}