{"id":"W4304889920","doi":"10.1007/978-1-0716-2617-7_12","title":"Application of GeneCloudOmics: Transcriptomic Data Analytics for Synthetic Biology","year":2022,"lang":"en","type":"article","venue":"Methods in molecular biology","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Lakehead University","funders":"","keywords":"Transcriptome; Computational biology; Profiling (computer programming); Gene expression profiling; RNA-Seq; Biology; Computer science; Gene; Gene expression; Bioinformatics; Genetics","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":[0.001857967,0.002038708,0.001000786,0.002884093,0.0007485614,0.002695835,0.00131682,0.000701856,0.004381876],"category_scores_gemma":[0.005023961,0.0006091468,0.001728173,0.003595608,0.0006350732,0.001755067,0.002376551,0.001596547,0.002259291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008443398,"about_ca_system_score_gemma":0.001899405,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002196384,"about_ca_topic_score_gemma":0.002681071,"domain_scores_codex":[0.9986394,0.0001832606,0.0001292389,0.0004207109,0.0005481791,0.0000791213],"domain_scores_gemma":[0.997991,0.0008543789,0.0002011234,0.0005077654,0.000293795,0.0001519622],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00203196,0.0005837385,0.02412688,0.002875614,0.001467917,0.001266559,0.00140207,0.04349108,0.3624328,0.04532231,0.08810544,0.4268937],"study_design_scores_gemma":[0.0001991521,0.0003509497,0.01575701,0.0002317148,0.0002718322,0.000830906,0.0005691653,0.5434572,0.1994425,0.1036406,0.1350251,0.0002238702],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02400413,0.0007248371,0.8152456,0.0009374442,0.0004009445,0.0004291949,0.04408767,0.110663,0.003507081],"genre_scores_gemma":[0.1641878,0.001411488,0.7417001,0.0008156198,0.0002128349,0.001091925,0.07911376,0.008891415,0.002575038],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004381876,"threshold_uncertainty_score":0.01465881,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05431122725318199,"score_gpt":0.4148817058128662,"score_spread":0.3605704785596842,"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."}}