{"id":"W2998705129","doi":"10.1016/j.trecan.2019.11.009","title":"Metabolic Fitness and Plasticity in Cancer Progression","year":2020,"lang":"en","type":"review","venue":"Trends in cancer","topic":"Cancer, Hypoxia, and Metabolism","field":"Biochemistry, Genetics and Molecular Biology","cited_by":135,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa; McGill University Health Centre","funders":"Fonds de Recherche du Québec - Santé; Terry Fox Research Institute; Canadian Institutes of Health Research; Fondation du cancer du sein du Québec","keywords":"Cancer cell; AMPK; Tumor microenvironment; Biology; Cancer; Cancer research; PI3K/AKT/mTOR pathway; Tumor progression; Hypoxia (environmental); Mechanistic target of rapamycin; Tumor hypoxia; Bioinformatics; Medicine; Protein kinase A; Kinase; Cell biology; Internal medicine; Signal transduction; Chemistry; Radiation therapy; Tumor cells","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":[0.0006916117,0.001021588,0.001662588,0.001345222,0.0002795585,0.00167117,0.001011397,0.001605315,0.004267478],"category_scores_gemma":[0.0007957751,0.0003127187,0.0003728349,0.002136567,0.0008168314,0.001484123,0.001008425,0.002603426,0.002292211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001251087,"about_ca_system_score_gemma":0.001136951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001517784,"about_ca_topic_score_gemma":0.003094082,"domain_scores_codex":[0.9998398,0.0000294347,0.00001726264,0.00003355277,0.00005871849,0.00002121297],"domain_scores_gemma":[0.9997378,0.0001103681,0.00003461379,0.000009456154,0.00006870873,0.00003906808],"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":[0.0001111216,0.00003916373,0.0001703721,0.007207885,0.00006899679,0.0001163998,0.00003190694,0.0004782001,0.00147445,0.008477116,0.05587165,0.9259528],"study_design_scores_gemma":[0.00002156815,0.00005670097,0.0009609203,0.001884965,0.00007590808,0.0003780867,0.00004374247,0.0001425182,0.0003309236,0.005694152,0.9903881,0.00002237716],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00004873245,0.9985796,0.000105164,0.0003938875,0.0002813738,0.000001840236,0.00001561694,0.000006444175,0.000567346],"genre_scores_gemma":[0.0004540648,0.9983953,0.00009094705,0.0002006297,0.0003247845,0.000004516583,0.00002403581,0.000001187401,0.0005044619],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004267478,"threshold_uncertainty_score":0.01427615,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05014580205412614,"score_gpt":0.3941794248408389,"score_spread":0.3440336227867128,"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."}}