{"id":"W2963537577","doi":"10.48550/arxiv.1606.04754","title":"A Correlational Encoder Decoder Architecture for Pivot Based Sequence\\n Generation","year":2016,"lang":"","type":"preprint","venue":"arXiv (Cornell University)","topic":"Algorithms and Data Compression","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Encoder; Sequence (biology); Architecture; Computer science; Soft-decision decoder; Arithmetic; Decoding methods; Computer architecture; Parallel computing; Algorithm; Mathematics; Operating system; Art; Genetics","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":[0.0007235452,0.0007006607,0.000565096,0.0003873461,0.0003913952,0.0007938808,0.002006308,0.001265673,0.006601035],"category_scores_gemma":[0.001489471,0.0005078122,0.000551045,0.0004133553,0.0006360848,0.00120865,0.001038297,0.001773393,0.003236858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000959171,"about_ca_system_score_gemma":0.001912852,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008219806,"about_ca_topic_score_gemma":0.01965897,"domain_scores_codex":[0.9996951,0.00006402648,0.00001696098,0.0001070074,0.00006594604,0.0000511096],"domain_scores_gemma":[0.9994975,0.0001723755,0.00003656018,0.0001077466,0.0001480817,0.00003761737],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006117323,0.0003364104,0.001756828,0.0002639093,0.0001672748,0.0006017617,0.0002557694,0.3617696,0.03816945,0.04339242,0.01398728,0.5386876],"study_design_scores_gemma":[0.00002326737,0.0000776387,0.0001403129,0.00001356142,0.00002398586,0.00008657564,0.00001198431,0.9784389,0.01165215,0.005956528,0.00356014,0.00001487051],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02258974,0.0005962287,0.9605793,0.0004776084,0.0001964435,0.0001035496,0.000376074,0.007596625,0.007484502],"genre_scores_gemma":[0.5691147,0.000481611,0.3981886,0.0006759274,0.0001152482,0.0002334411,0.001707015,0.0004279123,0.02905548],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008219806,"threshold_uncertainty_score":0.02208269,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1357752411613671,"score_gpt":0.2180369733358085,"score_spread":0.08226173217444135,"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."}}