{"id":"W3013076696","doi":"10.1115/1.0005443v","title":"Deep Convolutional Recurrent Autoencoders for Flow Field Prediction","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Model Reduction and Neural Networks","field":"Physics and Astronomy","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Convolutional neural network; Artificial intelligence; Deep learning; Field (mathematics); Recurrent neural network; Flow (mathematics); Artificial neural network; Mathematics","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00006570557,0.0001907159,0.000207573,0.00003693471,0.0001063275,0.00008169316,0.0001112002,0.0001465159,0.00342509],"category_scores_gemma":[0.000005518973,0.0001861039,0.0003056965,0.00004034849,0.0000191438,0.00005736771,0.0001366495,0.0004157908,0.000006391],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003448853,"about_ca_system_score_gemma":0.0001335209,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004652744,"about_ca_topic_score_gemma":0.000006813691,"domain_scores_codex":[0.998946,0.00002870045,0.0002598192,0.0004230438,0.0001401647,0.0002022905],"domain_scores_gemma":[0.9993979,0.0000623519,0.00009554671,0.0002228347,0.0001346536,0.00008669835],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001128766,0.0003419715,0.000937001,0.0001452934,0.0004567594,6.895993e-7,0.0002735289,0.6456773,0.00004767735,0.02097513,0.1638093,0.1672225],"study_design_scores_gemma":[0.0002688836,0.0000376067,0.00007176271,0.00005766808,0.00004684558,6.400333e-7,0.0001454282,0.9859649,0.000214058,0.005752506,0.007256197,0.00018349],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00211119,0.0001518552,0.9843939,0.0008774969,0.004389087,0.0004398997,0.00009260941,0.00007283037,0.00747111],"genre_scores_gemma":[0.9367164,0.00007294201,0.04592874,0.0003635834,0.005291084,0.0008288367,0.004971391,0.00004557468,0.005781447],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9384652,"threshold_uncertainty_score":0.9974859,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02373980412737724,"score_gpt":0.2695293920254205,"score_spread":0.2457895878980433,"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."}}