{"id":"W1985557809","doi":"10.1177/1534735414563603","title":"Personalized Integrative Oncology: Targeted Approaches for Optimal Outcomes","year":2014,"lang":"en","type":"article","venue":"Integrative Cancer Therapies","topic":"Complementary and Alternative Medicine Studies","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto","funders":"National Institute on Minority Health and Health Disparities; National Cancer Institute; National Institutes of Health; Lotte and John Hecht Memorial Foundation","keywords":"Integrative medicine; Medicine; Alternative medicine; Health care; Medical education; Oncology; Political science; Pathology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.01064453,0.0007271725,0.0008612745,0.001308284,0.001516207,0.004944006,0.0009606947,0.00287039,0.006076808],"category_scores_gemma":[0.01026993,0.0002511087,0.0008892344,0.0009081734,0.004353031,0.005189248,0.006741205,0.006967856,0.0009863282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002447238,"about_ca_system_score_gemma":0.006126952,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004673532,"about_ca_topic_score_gemma":0.001527966,"domain_scores_codex":[0.9940698,0.003996302,0.0002473247,0.0003142344,0.001034255,0.0003380613],"domain_scores_gemma":[0.9952998,0.003025245,0.0003052997,0.000260408,0.0003742707,0.0007349521],"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":[0.0001745899,0.0006334275,0.001719211,0.003904708,0.0001746283,0.0002869718,0.004198785,0.0008138355,0.001562904,0.2004967,0.1232857,0.6627485],"study_design_scores_gemma":[0.0002293861,0.0008906512,0.005962353,0.006161935,0.0001813983,0.001073155,0.004715197,0.0009515885,0.001710396,0.3317292,0.646284,0.0001107571],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.008142835,0.2461959,0.04918575,0.6068007,0.01117291,0.0005380466,0.0001535351,0.0003295512,0.07748071],"genre_scores_gemma":[0.2710843,0.4026488,0.1153354,0.1648383,0.0223789,0.002542088,0.0003406321,0.0002213305,0.02061009],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01064453,"threshold_uncertainty_score":0.05629438,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1016631633550312,"score_gpt":0.3928400910375522,"score_spread":0.2911769276825211,"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."}}