{"id":"W3120668689","doi":"10.1089/ten.tec.2020.0300","title":"Applications of Omics Technologies for Three-Dimensional <i>In Vitro</i> Disease Models","year":2021,"lang":"en","type":"review","venue":"Tissue Engineering Part C Methods","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Omics; Disease; Metabolomics; Leverage (statistics); Epigenomics; Proteomics; Computational biology; Systems biology; Emerging technologies; Genomics; Data science; Biology; Bioinformatics; Computer science; Medicine; Artificial intelligence; Genome; Pathology; DNA methylation; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003026849,0.0002599589,0.0007831421,0.0001002377,0.00001996473,0.00001059788,0.0002449695,0.0002813601,0.000001609195],"category_scores_gemma":[0.0002926241,0.0002725621,0.0002479631,0.0001726815,0.00003202595,0.000001732276,0.0001855943,0.0001310894,6.255137e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003081349,"about_ca_system_score_gemma":0.0002496098,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003345381,"about_ca_topic_score_gemma":0.00000218567,"domain_scores_codex":[0.9988672,0.00003049491,0.0004243846,0.0004036149,0.0000621269,0.0002121614],"domain_scores_gemma":[0.9989378,0.0002313542,0.0001338109,0.0005762308,0.00006181871,0.00005892336],"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":[0.000008149588,0.00003979872,1.383924e-7,0.003480371,0.00007986868,0.000001649316,0.000001599741,0.01494373,0.002220846,0.001043753,0.0002167845,0.9779633],"study_design_scores_gemma":[0.0001025053,0.00001942556,5.293653e-8,0.0005977186,0.0001859531,0.000003345507,0.000001199224,0.002838001,0.0094589,0.0002451016,0.9862866,0.0002611518],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00000136523,0.5997242,0.3992426,0.000007885234,0.0001204103,0.0005099642,0.0003724741,0.00001474058,0.000006320642],"genre_scores_gemma":[0.000005072064,0.7495226,0.2481195,0.000004901075,0.0001416853,0.001161052,0.0009306794,0.00005529919,0.00005922472],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9860699,"threshold_uncertainty_score":0.9999726,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03739352309677238,"score_gpt":0.3628080380771284,"score_spread":0.325414514980356,"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."}}