{"id":"W4241315037","doi":"10.1126/science.291.5510.1875b","title":"Can-Do Genome","year":2001,"lang":"en","type":"article","venue":"Science","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Genome; Biology; Computational biology; Genetics; Gene","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001307428,0.001234962,0.000849986,0.001682751,0.001903866,0.005989234,0.002212777,0.002745468,0.3499216],"category_scores_gemma":[0.005622398,0.000561993,0.0008429466,0.002150818,0.0007731771,0.003653139,0.00353399,0.002987701,0.3218435],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002203248,"about_ca_system_score_gemma":0.004165785,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04707494,"about_ca_topic_score_gemma":0.08482675,"domain_scores_codex":[0.9991816,0.00006252216,0.00002685262,0.0001501542,0.000408641,0.0001703163],"domain_scores_gemma":[0.9976539,0.0002469099,0.00007274085,0.0005263343,0.0006405308,0.0008595331],"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":[0.00002777144,0.000007190752,0.0001227053,0.00007137444,0.000005405579,0.00002333865,0.00005613116,0.00002431311,0.0004031278,0.003426503,0.9693327,0.02649935],"study_design_scores_gemma":[0.000006941738,0.000002404431,0.000159192,0.00002222619,0.000002596453,0.00001837066,0.00002453823,0.00002517777,0.0001088861,0.001069301,0.9985552,0.000005103183],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.001755462,0.007281305,0.01647666,0.04598041,0.01203726,0.0002789942,0.1620514,0.08085884,0.6732797],"genre_scores_gemma":[0.01622796,0.007837661,0.03142348,0.02382855,0.001948049,0.0003853255,0.2694158,0.02290313,0.62603],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3499216,"threshold_uncertainty_score":0.927258,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01729737222813839,"score_gpt":0.2943265990429806,"score_spread":0.2770292268148422,"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."}}