{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001883445,0.001863021,0.001833608,0.002563111,0.0008573005,0.002499709,0.002511555,0.001967117,0.3660869],"category_scores_gemma":[0.01025166,0.0006594386,0.001229419,0.004170302,0.0004662674,0.001780329,0.001638076,0.001629109,0.08394021],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001339704,"about_ca_system_score_gemma":0.002353235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007934987,"about_ca_topic_score_gemma":0.01520618,"domain_scores_codex":[0.9990566,0.0001304705,0.0001339602,0.0003782028,0.0001649511,0.0001358003],"domain_scores_gemma":[0.9959435,0.002477128,0.0003504448,0.0004633183,0.0005438322,0.0002217274],"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":[0.0003742847,0.0001140393,0.004794009,0.007694742,0.0002004342,0.000105423,0.00007298416,0.001167829,0.0006775682,0.001136918,0.9776408,0.006020944],"study_design_scores_gemma":[0.002414131,0.0001428728,0.01979977,0.002401673,0.0003206557,0.0002990827,0.0002329698,0.001676096,0.001469892,0.005244001,0.965887,0.0001119427],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00007077216,0.00002034414,0.0000509177,0.00001804224,0.00000494815,0.0000105139,0.9996432,0.00006326822,0.0001180271],"genre_scores_gemma":[0.0009586598,0.00005689592,0.0006771332,0.00007723497,0.000007802487,0.0001942715,0.9974363,0.00008170057,0.0005099196],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3660869,"threshold_uncertainty_score":0.9042001,"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."}}