{"id":"W2087992115","doi":"10.1016/j.chembiol.2011.06.001","title":"“Going KiNativ”: Probing the Native Kinome","year":2011,"lang":"en","type":"letter","venue":"Chemistry & Biology","topic":"Chronic Lymphocytic Leukemia Research","field":"Medicine","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Kinome; Biology; Kinase; Computational biology; Profiling (computer programming); Biochemistry; Computer science","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":[0.00457187,0.000732435,0.001360485,0.0005014192,0.006181209,0.004826709,0.00183434,0.04724349,0.006689935],"category_scores_gemma":[0.01854885,0.0006981582,0.0008280989,0.0004153999,0.008069847,0.008651447,0.003471707,0.05619149,0.004353754],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003760745,"about_ca_system_score_gemma":0.002758834,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002654897,"about_ca_topic_score_gemma":0.004513324,"domain_scores_codex":[0.997034,0.001402179,0.0001896109,0.0003415269,0.0006257921,0.0004069405],"domain_scores_gemma":[0.9921204,0.005536999,0.0002955214,0.000334891,0.0005166753,0.001195485],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001350424,0.00005415247,0.0005108221,0.00005426796,0.00002150834,0.001451689,0.0004081809,0.00007194626,0.0004155791,0.0155756,0.9655961,0.01570523],"study_design_scores_gemma":[0.000214245,0.0001187301,0.000777908,0.0001759692,0.00003747747,0.002942106,0.0015924,0.0006490955,0.000760582,0.1080222,0.8846169,0.00009250426],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"other","genre_scores_codex":[0.0004742045,0.001664003,0.0001744,0.9904715,0.005671495,0.000005665523,0.0000189074,0.00001832317,0.00150156],"genre_scores_gemma":[0.009085634,0.001512846,0.000343816,0.9709995,0.01363119,0.00003323957,0.00001819128,0.00001883445,0.004356746],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.04724349,"threshold_uncertainty_score":0.02728623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04041498815992353,"score_gpt":0.3051539833706344,"score_spread":0.2647389952107109,"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."}}