{"id":"W4386261709","doi":"10.59350/nf78q-yc933","title":"Target II: Monitoring a running goal in R","year":2021,"lang":"en","type":"preprint","venue":"","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":"Set (abstract data type); Quarter (Canadian coin); Mathematics; Computer science; History; Programming language","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004512757,0.0002728,0.0003092282,0.0001327647,0.00007678613,0.0001121667,0.0004970098,0.0006948533,0.0001014321],"category_scores_gemma":[0.000262178,0.0002557349,0.0001690635,0.0001083598,0.0001088866,0.000002503209,0.00300858,0.0006328193,0.0000116358],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004570621,"about_ca_system_score_gemma":0.0004688268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001370682,"about_ca_topic_score_gemma":0.00006238988,"domain_scores_codex":[0.9979818,0.00004403195,0.000482461,0.0005182188,0.0004324584,0.0005410024],"domain_scores_gemma":[0.9989563,0.00001040157,0.0000882544,0.0005809736,0.0001552882,0.000208811],"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":[0.0002778366,0.001149981,0.1586122,0.002445054,0.0006785037,0.0002463558,0.003228435,0.002748836,0.7576262,0.00005498868,0.01252842,0.0604032],"study_design_scores_gemma":[0.001973527,0.000749431,0.03300443,0.0008879742,0.00003620207,0.00002771425,0.003958615,0.004606779,0.8862922,0.0004765336,0.06618808,0.001798481],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9857516,0.002255392,0.002292884,0.0003135051,0.001052061,0.0003007617,0.00001722611,0.00002042031,0.007996203],"genre_scores_gemma":[0.9727373,0.001822698,0.02088395,0.000125313,0.0008434365,0.00004765888,0.0005125178,0.00002927451,0.002997926],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.128666,"threshold_uncertainty_score":0.9999895,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02234152855542149,"score_gpt":0.3068474254914689,"score_spread":0.2845058969360474,"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."}}