{"id":"W2406803433","doi":"10.1146/annurev-cancerbio-050216-121954","title":"Analyzing Tumor Metabolism In Vivo","year":2016,"lang":"en","type":"article","venue":"Annual Review of Cancer Biology","topic":"Cancer, Hypoxia, and Metabolism","field":"Biochemistry, Genetics and Molecular Biology","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institutes of Health Research; National Institutes of Health","keywords":"In vivo; Metabolomics; Positron emission tomography; Cancer; Phenotype; Metabolism; Cancer research; Biology; Metabolic pathway; In vivo magnetic resonance spectroscopy; Cancer cell; Metabolome; Disease; Bioinformatics; Magnetic resonance imaging; Mechanism (biology); Neuroscience; Pathology; Medicine; Biochemistry; Genetics; Gene; Radiology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002485408,0.000340751,0.000346097,0.0006791513,0.0002303123,0.0005718346,0.000178675,0.0004215243,0.002368511],"category_scores_gemma":[0.0001602239,0.0001880529,0.0001942952,0.0006294067,0.0002715673,0.0004954913,0.0003389441,0.000885442,0.001131971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003606126,"about_ca_system_score_gemma":0.0002749955,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008324887,"about_ca_topic_score_gemma":0.001043785,"domain_scores_codex":[0.9998761,0.00002322688,0.000005015592,0.00004072388,0.00003478289,0.00002004002],"domain_scores_gemma":[0.9999095,0.00002102302,0.0000183534,0.00001193759,0.00002050144,0.00001864509],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002996227,0.00003516639,0.002265322,0.0001523517,0.00002412692,0.0001097751,0.00006569671,0.0003340679,0.9778668,0.0008814243,0.000747906,0.01721782],"study_design_scores_gemma":[0.00002918537,0.0007797125,0.02734955,0.00005572126,0.0001181605,0.001507945,0.0002586767,0.004583672,0.9249318,0.002719665,0.03762604,0.00003983016],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"review","genre_scores_codex":[0.7331187,0.05372784,0.1600446,0.00141203,0.0005364181,0.0001722857,0.009239164,0.001863478,0.03988551],"genre_scores_gemma":[0.8904737,0.03999085,0.04245849,0.0008328492,0.0001529498,0.0003175434,0.006216522,0.0005065201,0.01905055],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.002368511,"threshold_uncertainty_score":0.007923484,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008651569174167205,"score_gpt":0.3094072134965778,"score_spread":0.3007556443224106,"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."}}