{"id":"W2176231757","doi":"10.1161/circgenetics.115.001219","title":"Finding the Therapeutic Sweet Spot","year":2015,"lang":"en","type":"letter","venue":"Circulation Cardiovascular Genetics","topic":"Genomics and Rare Diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"Canadian Institutes of Health Research","keywords":"Sweet spot; Medicine; Computer science; Simulation","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":[0.00248161,0.0006456754,0.001212085,0.0008115171,0.00235412,0.003250538,0.001052539,0.02558841,0.005703895],"category_scores_gemma":[0.0165478,0.0003836457,0.0007303766,0.0002709308,0.003610998,0.003871167,0.00214458,0.0335288,0.003101993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001963089,"about_ca_system_score_gemma":0.001549356,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006427983,"about_ca_topic_score_gemma":0.001294536,"domain_scores_codex":[0.998116,0.000703557,0.0001392194,0.0002891478,0.0004841503,0.0002678984],"domain_scores_gemma":[0.9951191,0.002857692,0.0001984223,0.0002198773,0.0004547882,0.001150102],"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":[0.0001267548,0.00009724784,0.0007675185,0.00009149844,0.00004119633,0.007560052,0.0001375224,0.0001637644,0.000467535,0.02090546,0.9402243,0.02941705],"study_design_scores_gemma":[0.0003593301,0.0002044412,0.0009030001,0.0005679199,0.00006635912,0.01186227,0.0006516449,0.001263254,0.0005687849,0.1064349,0.8770164,0.0001018246],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0005655289,0.00493294,0.0003677701,0.965995,0.02414299,0.000008604186,0.00001717204,0.00003904644,0.003930915],"genre_scores_gemma":[0.01368149,0.003417011,0.0006510848,0.8732964,0.1017975,0.00003678683,0.00002342733,0.00002573011,0.007070672],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.02558841,"threshold_uncertainty_score":0.01908141,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03242586616792502,"score_gpt":0.2456205565234296,"score_spread":0.2131946903555046,"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."}}