{"id":"W4287545976","doi":"10.48550/arxiv.2012.15458","title":"Differentiable Programming à la Moreau","year":2020,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Neural Networks and Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institute for Advanced Research; National Science Foundation","keywords":"Differentiable function; Computer science; Envelope (radar); Automatic differentiation; Artificial intelligence; Mathematical optimization; Theoretical computer science; Programming language; Mathematics; Computation; Pure mathematics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00196084,0.0009486082,0.0008505815,0.0009100154,0.001003518,0.003798414,0.0007082658,0.001623368,0.007099879],"category_scores_gemma":[0.004170363,0.0004928304,0.001464238,0.001264542,0.004272241,0.004690086,0.002175616,0.005537021,0.002643764],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002283839,"about_ca_system_score_gemma":0.001353658,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002499092,"about_ca_topic_score_gemma":0.001466069,"domain_scores_codex":[0.9989948,0.0003127587,0.00004180556,0.0002213168,0.0003419736,0.00008735168],"domain_scores_gemma":[0.9991153,0.0004511235,0.00006223759,0.0001447665,0.0001682184,0.0000583328],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000006454218,0.000005837616,0.00003366744,0.00002181018,0.000004534181,0.00001555555,0.00004298057,0.002208715,0.000159106,0.9892676,0.001657955,0.006575654],"study_design_scores_gemma":[0.000007917722,0.00001222595,0.00005223968,0.00003387795,0.000004623575,0.00003255852,0.00001454479,0.01928855,0.0002954599,0.9569566,0.0232915,0.000009939283],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.008407845,0.004967913,0.8882459,0.006249107,0.0006577616,0.00003733915,0.0002867322,0.0004080981,0.09073934],"genre_scores_gemma":[0.4707213,0.009318966,0.4331451,0.004371578,0.002108912,0.0004491323,0.0004634226,0.001151616,0.07827011],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007099879,"threshold_uncertainty_score":0.02375144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08405163039584398,"score_gpt":0.1902851060548076,"score_spread":0.1062334756589636,"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."}}