{"id":"W2316755250","doi":"10.1016/j.canlet.2016.04.009","title":"Targeting tumor microenvironment in cancer therapy","year":2016,"lang":"en","type":"editorial","venue":"Cancer Letters","topic":"Cancer Research and Treatments","field":"Biochemistry, Genetics and Molecular Biology","cited_by":52,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University Health Centre","funders":"","keywords":"Tumor microenvironment; Cancer; Cancer therapy; Cancer research; Medicine; Oncology; Internal medicine","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":[0.006818131,0.003811261,0.003254211,0.002405672,0.002908541,0.007224366,0.003325543,0.01857978,0.007406821],"category_scores_gemma":[0.01062377,0.001505116,0.002091822,0.0009811004,0.002853617,0.004626432,0.002575276,0.03055646,0.005816758],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003421037,"about_ca_system_score_gemma":0.002660593,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001145808,"about_ca_topic_score_gemma":0.003856772,"domain_scores_codex":[0.9956062,0.0008919667,0.0005095829,0.0003723515,0.002261125,0.0003586751],"domain_scores_gemma":[0.9920446,0.003264741,0.0006497686,0.0002344541,0.002170558,0.001635888],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006648499,0.00002165117,0.00002080267,0.0002270349,0.0000198165,0.0001578336,0.00001378644,0.00004413016,0.0002040011,0.0007793883,0.9883977,0.01004735],"study_design_scores_gemma":[0.00008527082,0.000045751,0.0001413544,0.0001967464,0.00005342706,0.0003196468,0.00002189614,0.0002321589,0.0002952903,0.001441095,0.997151,0.00001649626],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.00006436042,0.01785881,0.0002515448,0.06122762,0.9185314,0.00002341751,0.00003007389,0.00006276144,0.001950101],"genre_scores_gemma":[0.0007650948,0.01108661,0.0002024118,0.03245603,0.9408931,0.0000290593,0.00001950874,0.00002847852,0.01451968],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.01857978,"threshold_uncertainty_score":0.03605813,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00780497715020416,"score_gpt":0.2958318804229462,"score_spread":0.288026903272742,"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."}}