{"id":"W3034297959","doi":"","title":"Time-aware Large Kernel Convolutions","year":2020,"lang":"en","type":"article","venue":"","topic":"Topic Modeling","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Kernel (algebra); Softmax function; Sequence (biology); Automatic summarization; Convolution (computer science); Algorithm; Computational complexity theory; Artificial intelligence; Theoretical computer science; Deep learning; Mathematics; Artificial neural network; Discrete 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008017852,0.0008125308,0.0008704591,0.000619214,0.0004102167,0.0007759938,0.001275329,0.0008275431,0.003350844],"category_scores_gemma":[0.003339139,0.0003456138,0.0009583677,0.0009332479,0.0005202663,0.00249359,0.001146294,0.001195588,0.001589042],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001076752,"about_ca_system_score_gemma":0.00104567,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005984527,"about_ca_topic_score_gemma":0.008675354,"domain_scores_codex":[0.9994851,0.0001023616,0.00003796042,0.0001765176,0.0001179521,0.00007999639],"domain_scores_gemma":[0.999016,0.0004354788,0.0000873019,0.0002398728,0.0001591085,0.00006219569],"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":[0.0005693858,0.0001524464,0.001928505,0.0001972434,0.0001204283,0.0001954015,0.0002902602,0.2951791,0.04755221,0.03088731,0.007095311,0.6158324],"study_design_scores_gemma":[0.000005292229,0.00002006466,0.0002310025,0.000003634986,0.00001163947,0.00004608199,0.00001465672,0.9831604,0.008061414,0.007307934,0.001129337,0.000008430127],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02764222,0.0003555506,0.9672343,0.0001463397,0.00005462231,0.00002626036,0.000150357,0.003279069,0.001111358],"genre_scores_gemma":[0.6585234,0.000430336,0.3313039,0.0002091685,0.0001138443,0.0001102926,0.0009277492,0.0005953312,0.007786031],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005984527,"threshold_uncertainty_score":0.01189935,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.028168816217734,"score_gpt":0.2373646437574095,"score_spread":0.2091958275396754,"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."}}