{"id":"W6892030206","doi":"10.48660/23120027","title":"Deep Learning Convolutions Through the Lens of Tensor Networks","year":2023,"lang":"en","type":"other","venue":"PIRSA","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Vector Institute","funders":"","keywords":"Deep learning; Lens (geology); Tensor (intrinsic definition); Focus (optics); Convolution (computer science); Convolutional neural network","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":["insufficient_payload"],"category_scores_codex":[0.0002348309,0.0002993346,0.0004366861,0.0001238705,0.00014615,0.00002045911,0.0004030272,0.0003443331,0.002566956],"category_scores_gemma":[0.0002600117,0.0002204606,0.0002010786,0.0005913112,0.0003747788,0.00004402395,0.0001413912,0.0007469538,0.01224776],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000867177,"about_ca_system_score_gemma":0.00004213859,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001651116,"about_ca_topic_score_gemma":0.004136503,"domain_scores_codex":[0.9984058,0.0002058379,0.000276825,0.0003392597,0.0003159411,0.000456407],"domain_scores_gemma":[0.998494,0.0003166244,0.0004586442,0.0006306298,0.0000670619,0.00003306362],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000009410977,0.00004002268,0.0006633548,0.00003853027,0.0004343296,0.000007307352,0.0006655259,0.02027481,0.00002261212,0.005345544,0.9719413,0.0005572915],"study_design_scores_gemma":[0.0002195528,0.0000250063,0.0007701431,0.000240109,0.000198189,0.000003422598,0.0002974357,0.004859462,0.000001477824,0.0000701618,0.9930675,0.0002475263],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.00001382182,0.006636093,0.003506981,0.0002097809,0.0007891841,0.000573733,0.0001208749,0.002354806,0.9857947],"genre_scores_gemma":[0.01092809,0.001248001,0.0004717516,0.00008984539,0.001376398,0.00008908785,0.00009613351,0.0049421,0.9807586],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.02112625,"threshold_uncertainty_score":0.9983448,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03104693986403707,"score_gpt":0.2704903511652101,"score_spread":0.2394434113011731,"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."}}