{"id":"W2076210163","doi":"10.1158/1538-7445.am2014-5340","title":"Abstract 5340: Bioinformatic analyses approaches for personalized oncogenomics","year":2014,"lang":"en","type":"article","venue":"Cancer Research","topic":"Lung Cancer Treatments and Mutations","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Cancer Agency","funders":"","keywords":"Transcriptome; Genome; Biology; Computational biology; Genetics; Cancer genome sequencing; Genomics; Whole genome sequencing; DNA sequencing; Gene; Gene expression","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":[0.005836103,0.001356929,0.00136486,0.00362289,0.0007230059,0.004461773,0.001654608,0.0009933298,0.01084862],"category_scores_gemma":[0.009507117,0.0007625961,0.001676921,0.003196262,0.0009380172,0.002223691,0.002381091,0.001736753,0.005616555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00112917,"about_ca_system_score_gemma":0.001065243,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001305035,"about_ca_topic_score_gemma":0.001410073,"domain_scores_codex":[0.9967844,0.001344829,0.0002224106,0.0006465578,0.0009078797,0.00009390732],"domain_scores_gemma":[0.9953146,0.002670789,0.0002837158,0.0007686629,0.0007890009,0.0001732621],"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":[0.0005095738,0.000313252,0.008448273,0.002001813,0.0009954952,0.0006480898,0.0006086348,0.06851219,0.05033585,0.07082263,0.08886863,0.7079356],"study_design_scores_gemma":[0.0001032438,0.0001381016,0.01058286,0.0003779776,0.0002318878,0.0004625297,0.0003021184,0.5090257,0.02019034,0.3098013,0.1486164,0.000167564],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.005216714,0.001769572,0.9597044,0.001978202,0.0002365182,0.0002141313,0.006011013,0.02040808,0.004461439],"genre_scores_gemma":[0.05980717,0.001889073,0.9169441,0.0009380229,0.0003207375,0.0005564414,0.01241452,0.003425451,0.003704494],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.01084862,"threshold_uncertainty_score":0.0362922,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3629766902880875,"score_gpt":0.529471534395429,"score_spread":0.1664948441073415,"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."}}