{"id":"W2618094628","doi":"10.1200/edbk_173836","title":"Bench-to-Bedside Approaches for Personalized Exercise Therapy in Cancer","year":2017,"lang":"en","type":"review","venue":"American Society of Clinical Oncology Educational Book","topic":"Cancer survivorship and care","field":"Medicine","cited_by":47,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia, Okanagan Campus","funders":"","keywords":"Medicine; Bench to bedside; Exercise prescription; Personalization; Cancer therapy; Disease; Medical prescription; Cancer; Intensive care medicine; Physical therapy; Precision oncology; Precision medicine; Oncology; Internal medicine; Medical physics; Pharmacology; Pathology; Computer science","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":[0.001292011,0.0003813247,0.004861397,0.00008821454,0.00008972469,0.00001034448,0.0004399695,0.0005222523,0.0005199775],"category_scores_gemma":[0.0004899004,0.0003118204,0.002855145,0.0002173445,0.001594153,0.00005111946,0.00006604478,0.0007083389,0.00001471377],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005626855,"about_ca_system_score_gemma":0.01458351,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001206345,"about_ca_topic_score_gemma":0.0002419717,"domain_scores_codex":[0.9967383,0.0002239795,0.001619148,0.0007418253,0.0003161292,0.000360641],"domain_scores_gemma":[0.9933297,0.003701382,0.001746218,0.0005871881,0.0002982728,0.0003372314],"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":[0.0002814245,0.0008190048,0.0008821871,0.002138272,0.0004669709,5.377832e-7,0.001028799,4.004206e-7,5.881375e-8,0.000196721,0.04852514,0.9456605],"study_design_scores_gemma":[0.001254166,0.001025144,0.002003758,0.003275435,0.000757767,0.000004268662,0.0006757519,0.000003970176,1.872477e-7,0.0000950614,0.9906258,0.0002786927],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0001070078,0.9740301,0.00002250959,0.02020917,0.0008972632,0.00247697,0.0001375712,0.00001278717,0.00210663],"genre_scores_gemma":[0.00003265958,0.9592159,0.003257539,0.007788154,0.001587742,0.003732749,0.0002606426,0.00006031185,0.02406432],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9453818,"threshold_uncertainty_score":0.9999334,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4677373705741588,"score_gpt":0.5789959447128415,"score_spread":0.1112585741386828,"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."}}