{"id":"W2999167819","doi":"10.3390/molecules25020325","title":"In Depth Analysis of Kinase Cross Screening Data to Identify CAMKK2 Inhibitory Scaffolds","year":2020,"lang":"en","type":"article","venue":"Molecules","topic":"Melanoma and MAPK Pathways","field":"Biochemistry, Genetics and Molecular Biology","cited_by":37,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Center for Advancing Translational Sciences; National Health and Medical Research Council; Novartis Pharma; National Institutes of Health; Medical Research Council; Ministero dello Sviluppo Economico; Genome Canada; Fundação de Amparo à Pesquisa do Estado de São Paulo; National Cancer Institute; European Federation of Pharmaceutical Industries and Associations; Merck KGaA; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Ontario Ministry of Economic Development and Innovation; Pfizer","keywords":"AMPK; Kinase; Protein kinase A; Enzyme; Biochemistry; Chemistry; Biology; Cell biology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001573862,0.0001285603,0.000228308,0.0001284025,0.00002905155,0.00002632142,0.0004781664,0.0000999255,0.00002173577],"category_scores_gemma":[0.0001389443,0.0001350694,0.00009209292,0.0005022897,0.00004335814,0.00000783378,0.0005658445,0.00004293053,0.000009082063],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000494401,"about_ca_system_score_gemma":0.00003878864,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000136306,"about_ca_topic_score_gemma":0.0003438942,"domain_scores_codex":[0.9988288,0.00005759643,0.0002699709,0.0004916414,0.0001523447,0.0001997022],"domain_scores_gemma":[0.9991247,0.000008385744,0.00007045735,0.0006088379,0.00004840121,0.0001391864],"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":[0.00007073852,0.00003090487,0.02442826,0.00002621331,0.000167005,0.00003966014,0.0001058829,0.001005024,0.9713448,0.00002530578,0.002128594,0.0006276302],"study_design_scores_gemma":[0.0004608245,0.0001720637,0.09870598,0.0000182866,0.0001684612,0.000001627402,0.000103756,0.00182854,0.8904781,0.000004476511,0.007802799,0.0002550477],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9897532,0.0004325412,0.008912522,0.0002033454,0.00005196599,0.0001092516,0.0001816125,0.000008234901,0.0003472937],"genre_scores_gemma":[0.9964343,0.0000154989,0.002001252,0.0007769402,0.00009793828,0.000007533405,0.0005978709,0.00001626877,0.00005234781],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08086664,"threshold_uncertainty_score":0.5507971,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05823401505428979,"score_gpt":0.3414051645644878,"score_spread":0.2831711495101981,"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."}}