{"id":"W2940292305","doi":"10.1038/s41592-019-0405-z","title":"Author Correction: Two-level factorial experiments","year":2019,"lang":"en","type":"erratum","venue":"Nature Methods","topic":"Optimal Experimental Design Methods","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre","funders":"","keywords":"Column (typography); Table (database); Factorial experiment; Factorial; Fractional factorial design; Computer science; Statistics; Error detection and correction; Mathematics; Algorithm; Data mining; Telecommunications","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":[0.0118388,0.00295325,0.003112403,0.005579825,0.003833694,0.003693855,0.005202757,0.006229851,0.1558025],"category_scores_gemma":[0.1449367,0.001914334,0.002325946,0.003376627,0.002656123,0.002893165,0.002732092,0.009648294,0.0588646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003714103,"about_ca_system_score_gemma":0.006616198,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008817879,"about_ca_topic_score_gemma":0.0163645,"domain_scores_codex":[0.9845837,0.004082501,0.002246954,0.001937623,0.006619297,0.0005298991],"domain_scores_gemma":[0.8682081,0.03966499,0.003301023,0.01337763,0.07326251,0.002185863],"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":[0.00006673393,0.00001110871,0.00004529918,0.000270398,0.00002244545,0.00008458878,0.00002724474,0.00008499384,0.0001298233,0.001401785,0.9894726,0.008382909],"study_design_scores_gemma":[0.0001580992,0.00003054158,0.0006024332,0.0005291547,0.0001151792,0.0003369704,0.00006326727,0.0008343988,0.001223596,0.006624974,0.9894058,0.00007562256],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.0001782628,0.0005515463,0.008729598,0.01507615,0.9665343,0.00009350315,0.00324903,0.001667777,0.003919905],"genre_scores_gemma":[0.0239814,0.004347558,0.1146756,0.06996276,0.195111,0.001850521,0.01142735,0.01402033,0.5646235],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1558025,"threshold_uncertainty_score":0.5212114,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2813980481515689,"score_gpt":0.5840002347499562,"score_spread":0.3026021865983873,"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."}}