{"id":"W2470644820","doi":"10.1038/ncomms12156","title":"ERRα mediates metabolic adaptations driving lapatinib resistance in breast cancer","year":2016,"lang":"en","type":"article","venue":"Nature Communications","topic":"Metabolism, Diabetes, and Cancer","field":"Biochemistry, Genetics and Molecular Biology","cited_by":117,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hôpital du Sacré-Cœur de Montréal; McGill University","funders":"Congressionally Directed Medical Research Programs; Terry Fox Research Institute; Canadian Institutes of Health Research; Fondation du cancer du sein du Québec; McGill University; U.S. Department of Defense","keywords":"Lapatinib; Cancer research; Breast cancer; Cancer; Pharmacology; PI3K/AKT/mTOR pathway; Cancer cell; Receptor tyrosine kinase; Medicine; Biology; Receptor; Internal medicine; Trastuzumab; Signal transduction; Cell biology","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":[0.0001637147,0.0002771317,0.0003277164,0.000192915,0.0001432835,0.0004091445,0.0001712176,0.0003010853,0.001293104],"category_scores_gemma":[0.0001227844,0.0001422568,0.0002108455,0.0001416912,0.000206555,0.0001868948,0.000239062,0.0005170659,0.000569559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002617832,"about_ca_system_score_gemma":0.0001015808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000216128,"about_ca_topic_score_gemma":0.0004162191,"domain_scores_codex":[0.9998837,0.00002701289,0.00000983455,0.00002111651,0.00002549879,0.00003281615],"domain_scores_gemma":[0.999922,0.000007939042,0.00003529228,0.00001031979,0.000008241146,0.00001624325],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005358655,0.00003583706,0.001266311,0.0000533769,0.00001204625,0.0004010821,0.00001595492,0.0001726686,0.9932655,0.0002437536,0.0001541951,0.00384324],"study_design_scores_gemma":[0.00009010523,0.001043299,0.03594992,0.00002437852,0.00005031203,0.005099936,0.0001614519,0.001765907,0.944394,0.0007823661,0.01061545,0.00002290886],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9866682,0.007255625,0.00252019,0.0005986502,0.00006289606,0.00001335174,0.0002963635,0.0001313687,0.002453347],"genre_scores_gemma":[0.9945987,0.002770479,0.0006099125,0.000145497,0.00002359665,0.000007816239,0.0002577839,0.00001874614,0.00156748],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001293104,"threshold_uncertainty_score":0.004325807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01211716495112047,"score_gpt":0.2900438727147905,"score_spread":0.2779267077636701,"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."}}