{"id":"W3022336006","doi":"10.1007/978-3-030-47358-7_3","title":"Investigating Relational Recurrent Neural Networks with Variable Length Memory Pointer","year":2020,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Domain Adaptation and Few-Shot Learning","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Pointer (user interface); Encoder; ENCODE; Sentence; Auxiliary memory; Artificial intelligence; Theoretical computer science; Computer hardware; Operating system","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":[0.0007488803,0.0005139153,0.0004441606,0.0003965562,0.0003715976,0.0006337046,0.001877417,0.0002273478,0.0000488551],"category_scores_gemma":[0.0001720805,0.0004473887,0.00008911094,0.0008151665,0.0005729156,0.0008373111,0.0009324674,0.001679644,0.00003003235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002131698,"about_ca_system_score_gemma":0.0005250865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008233197,"about_ca_topic_score_gemma":0.00001366974,"domain_scores_codex":[0.9961881,0.00007944307,0.0005499825,0.001500884,0.001092851,0.0005887231],"domain_scores_gemma":[0.9977047,0.0005901698,0.0004192606,0.0007397377,0.0002355203,0.0003106072],"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":[0.000006690741,0.00001076425,0.00008556189,0.00001995917,0.00001369497,0.0000439786,0.0009122659,0.7027348,0.00001053436,0.05499923,0.00004176178,0.2411208],"study_design_scores_gemma":[0.0003874156,0.0001956012,0.0001319828,0.0003480804,0.000007702428,0.00008016523,5.494516e-7,0.9791101,0.00001964766,0.0176178,0.001562384,0.0005385507],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00003354465,0.0002233609,0.9873477,0.00183857,0.001357006,0.0002987078,0.000001756691,0.0002336208,0.008665736],"genre_scores_gemma":[0.09196845,0.000009101792,0.8998681,0.006896888,0.0007759695,0.000010579,0.0000195679,0.00005450371,0.0003968749],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2763753,"threshold_uncertainty_score":0.9997978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02520679725633494,"score_gpt":0.2292489630197404,"score_spread":0.2040421657634055,"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."}}