{"id":"W3012165066","doi":"","title":"FuDGE: Functional Differential Graph Estimation with fully and discretely observed curves.","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Booth University College","funders":"","keywords":"Functional data analysis; Generalization; Graph; Graphical model; Lasso (programming language); Mathematics; Function (biology); Computer science; Algorithm; Applied mathematics; Theoretical computer science; Artificial intelligence; Machine learning; Mathematical analysis","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001070212,0.0003131739,0.0003332382,0.00006178665,0.0001246914,0.0006485062,0.0005822941,0.0001654788,0.00006256366],"category_scores_gemma":[0.00002480162,0.0002610024,0.00008281646,0.0001814207,0.00008343338,0.0002920885,0.000957058,0.00055929,0.00001353165],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002079681,"about_ca_system_score_gemma":0.000213721,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001815812,"about_ca_topic_score_gemma":0.00005971257,"domain_scores_codex":[0.9980365,0.00007127741,0.0002920503,0.0009058948,0.0004607608,0.0002334897],"domain_scores_gemma":[0.9989029,0.00004822742,0.0001567406,0.0005436054,0.000142534,0.0002060635],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006485425,0.000969776,0.01290509,0.01001323,0.001975759,0.0002453701,0.002432383,0.04326385,0.002896262,0.4360672,0.06122888,0.4273537],"study_design_scores_gemma":[0.0003532364,0.0001544989,0.02201875,0.0004651903,0.00005253339,0.00002098974,0.000004539131,0.9175501,0.0001259531,0.05868383,0.00002036087,0.000549982],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009885572,0.0003118917,0.9843792,0.003983717,0.0003748701,0.0002508267,0.00001534335,0.0003984668,0.000400084],"genre_scores_gemma":[0.857231,0.000150379,0.1412756,0.0007986039,0.00009323416,0.00005888742,0.0001566478,0.00001782792,0.0002178383],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8742863,"threshold_uncertainty_score":0.9999842,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07448944077871525,"score_gpt":0.245129382866863,"score_spread":0.1706399420881477,"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."}}