{"id":"W2792447269","doi":"10.1111/eva.12608","title":"Turning natural adaptations to oncogenic factors into an ally in the war against cancer","year":2018,"lang":"en","type":"article","venue":"Evolutionary Applications","topic":"Nutrition, Genetics, and Disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada; Fisheries and Oceans Canada","funders":"Institut écologie et environnement; Centre National de la Recherche Scientifique; Agence Nationale de la Recherche","keywords":"Biology; Cancer; Natural (archaeology); Adaptation (eye); Ecology; Genetics; Neuroscience","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":[0.001571404,0.000455648,0.0005432079,0.0008518967,0.00106712,0.002325337,0.000552361,0.002031331,0.00302291],"category_scores_gemma":[0.001500191,0.0001846699,0.0003224178,0.0006844433,0.005344282,0.003088761,0.002194755,0.00169985,0.0004572778],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001234214,"about_ca_system_score_gemma":0.001293462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006350112,"about_ca_topic_score_gemma":0.001168256,"domain_scores_codex":[0.9994091,0.0002367726,0.00002376626,0.0001506359,0.00009057548,0.00008930213],"domain_scores_gemma":[0.9992428,0.0002808208,0.0001585353,0.00009129976,0.00008173473,0.0001448015],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0007093659,0.0003132726,0.02270234,0.001984477,0.0002927489,0.001485478,0.003438443,0.004942908,0.1976774,0.3652444,0.005316096,0.3958931],"study_design_scores_gemma":[0.00005969933,0.001152588,0.04991373,0.0009271443,0.0002266021,0.00243401,0.008242944,0.002628564,0.05768152,0.4691369,0.4074279,0.0001685527],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4304551,0.2850894,0.07631119,0.1149527,0.002493799,0.0001012143,0.0003790729,0.0005070847,0.08971032],"genre_scores_gemma":[0.8881947,0.08289663,0.01538099,0.006208736,0.0006216249,0.0000414824,0.00007155223,0.00005968273,0.006524611],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00302291,"threshold_uncertainty_score":0.01011264,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01110348923808335,"score_gpt":0.2922250599016473,"score_spread":0.2811215706635639,"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."}}