{"id":"W4210735328","doi":"10.1109/icmla52953.2021.00231","title":"PrunedCaps: A Case For Primary Capsules Discrimination","year":2021,"lang":"en","type":"article","venue":"2021 20th IEEE International Conference on Machine Learning and Applications (ICMLA)","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"MNIST database; Computer science; Convolutional neural network; Artificial intelligence; Robustness (evolution); Affine transformation; Pruning; Contextual image classification; Deep learning; Pattern recognition (psychology); Architecture; Routing (electronic design automation); Machine learning; Image (mathematics); Mathematics; Embedded 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":[],"consensus_categories":[],"category_scores_codex":[0.0001743957,0.0002146565,0.0001918412,0.0001319134,0.0005050725,0.0003178235,0.0004461389,0.00007394531,0.00004859921],"category_scores_gemma":[0.00008022867,0.0002206669,0.00007873688,0.0003476776,0.00007173681,0.0003994709,0.0001586725,0.0003366903,0.00003505465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007702404,"about_ca_system_score_gemma":0.0001102906,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002095776,"about_ca_topic_score_gemma":0.00005630441,"domain_scores_codex":[0.9983432,0.00007749991,0.0003249984,0.000743256,0.0002718861,0.0002391724],"domain_scores_gemma":[0.9985161,0.000280135,0.0002060291,0.0004027929,0.0004744587,0.0001204454],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001411475,0.0001700531,0.0002024828,0.00003244199,0.00004156391,0.00004218009,0.000159223,0.001579804,0.007535022,0.7509488,0.0003865214,0.2388878],"study_design_scores_gemma":[0.001285456,0.0001664017,0.000507243,0.0001120859,0.00005329146,0.00102198,0.0003500368,0.6553445,0.004916896,0.05049183,0.2849506,0.0007996344],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003677937,0.0002767988,0.9735479,0.01013916,0.0002163742,0.0005878173,0.00009020167,0.0001784406,0.01128541],"genre_scores_gemma":[0.9089428,0.001090982,0.07863697,0.0007589862,0.0005891146,0.001987569,0.0005976079,0.00003796117,0.007358003],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9052649,"threshold_uncertainty_score":0.8998533,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04282396396391006,"score_gpt":0.3316449641870837,"score_spread":0.2888210002231736,"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."}}