{"id":"W2297663221","doi":"10.1158/1557-3125.modorg-b15","title":"Abstract B15: Optimization of an oncogenomics-based in vivo screen to validate candidate sarcoma genes","year":2014,"lang":"en","type":"article","venue":"Molecular Cancer Research","topic":"Virus-based gene therapy research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mount Sinai Hospital; Lunenfeld-Tanenbaum Research Institute","funders":"","keywords":"Zebrafish; Biology; Rhabdomyosarcoma; Gene; Cancer research; Carcinogenesis; PAX3; Candidate gene; Computational biology; Sarcoma; Genetics; Medicine; Pathology","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":[0.0005506633,0.0006143862,0.0004939606,0.0007117551,0.0002175027,0.0004022692,0.0003508983,0.0005956184,0.00329759],"category_scores_gemma":[0.0003319938,0.0002297263,0.0003898847,0.0004282803,0.0002297287,0.0001626264,0.0003209971,0.0005967433,0.001283168],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003488764,"about_ca_system_score_gemma":0.000533598,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001022216,"about_ca_topic_score_gemma":0.00177245,"domain_scores_codex":[0.9994733,0.00008308014,0.00004521411,0.00009671643,0.0002119269,0.00008978001],"domain_scores_gemma":[0.9996758,0.00008696903,0.00006045474,0.00004357574,0.00006993471,0.000063317],"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":[0.00005510878,0.00006968462,0.0001833237,0.0000165547,0.000004135508,0.00003425337,0.000004768842,0.000260874,0.9978855,0.00005367522,0.00006861852,0.001363448],"study_design_scores_gemma":[0.00001797572,0.0006377575,0.001611529,0.000004183034,0.00001656244,0.0001078044,0.00001151388,0.001099128,0.9939115,0.00003233797,0.002544186,0.000005496953],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9198326,0.0008129606,0.05961231,0.0003273723,0.00008462248,0.001899701,0.009044346,0.001024863,0.007361138],"genre_scores_gemma":[0.8728129,0.0009883658,0.09353478,0.0003374436,0.00001533826,0.001165397,0.01398597,0.0004207262,0.01673915],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00329759,"threshold_uncertainty_score":0.01103157,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03462795234101454,"score_gpt":0.3731418012412991,"score_spread":0.3385138489002846,"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."}}