{"id":"W2885686369","doi":"10.1158/1538-7445.am2018-3211","title":"Abstract 3211: Therapeutic effects of radiotherapy on cancer cell lines using <i>RadioGx</i> computational platform","year":2018,"lang":"en","type":"article","venue":"Cancer Research","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre","funders":"","keywords":"Radiogenomics; Medicine; Clonogenic assay; Radiosensitivity; Cancer; Pharmacogenomics; Oncology; Radiation therapy; Cancer research; Drug response; Internal medicine; Cell culture; Drug; Pharmacology; Biology; Radiomics","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":[0.0006188726,0.001188543,0.0008523774,0.0006249973,0.0003366667,0.0009084468,0.001156422,0.0009446092,0.005897839],"category_scores_gemma":[0.001191079,0.0003927973,0.001740374,0.0006134625,0.0003758855,0.0003204525,0.0005092596,0.0007229825,0.0007133231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001181199,"about_ca_system_score_gemma":0.001133318,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01141904,"about_ca_topic_score_gemma":0.009307999,"domain_scores_codex":[0.9998079,0.00005125409,0.00001053072,0.00006534993,0.00004430358,0.00002070327],"domain_scores_gemma":[0.9995314,0.0003207232,0.00003026401,0.00004149432,0.00005357651,0.00002251058],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004135576,0.0002031401,0.007728233,0.0005304984,0.000258561,0.000212834,0.00006494389,0.9618356,0.006446579,0.002117526,0.01019824,0.009990172],"study_design_scores_gemma":[0.0001342643,0.0001873238,0.002364833,0.00001644,0.00005717442,0.00004494212,0.00002743282,0.9870278,0.004920422,0.001301942,0.003894516,0.00002302263],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8343843,0.00126005,0.05237339,0.001506525,0.0003196665,0.0003463555,0.08196194,0.01232135,0.01552653],"genre_scores_gemma":[0.8426346,0.0007512504,0.06193244,0.0007009583,0.00005911003,0.000970458,0.08779079,0.0009831174,0.004177283],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01141904,"threshold_uncertainty_score":0.0227052,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06281588839087622,"score_gpt":0.4038357983490968,"score_spread":0.3410199099582206,"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."}}