{"id":"W4403345809","doi":"10.48550/arxiv.2410.07081","title":"JPEG Inspired Deep Learning","year":2024,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Computational Physics and Python Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Artificial intelligence; Computer science; Deep learning","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00051893,0.0007654408,0.0006346554,0.0005826248,0.0002465467,0.0006686399,0.001536895,0.0009353658,0.00385754],"category_scores_gemma":[0.001893713,0.0002536091,0.000445628,0.0006943084,0.0006032481,0.001197044,0.001048336,0.001853179,0.001080427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001012602,"about_ca_system_score_gemma":0.0009316569,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004304768,"about_ca_topic_score_gemma":0.007956803,"domain_scores_codex":[0.9997414,0.00003693079,0.00001008045,0.00006882309,0.0001027712,0.00004004378],"domain_scores_gemma":[0.9996538,0.0001335721,0.00003160832,0.00006916914,0.00007982568,0.00003204371],"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":[0.0001517864,0.0001618297,0.001460483,0.0002253976,0.00008975862,0.000108562,0.00005462036,0.5013547,0.007338626,0.03984749,0.03492182,0.4142849],"study_design_scores_gemma":[0.00001216477,0.00002360945,0.0000979974,0.00001136078,0.000005616523,0.00002612094,0.000003689618,0.9841776,0.001893814,0.01100828,0.002734888,0.00000485987],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0335921,0.002665754,0.9434433,0.001323131,0.0003886555,0.0001036128,0.001119573,0.005291812,0.01207206],"genre_scores_gemma":[0.5812827,0.001874855,0.3859983,0.002162655,0.0002749691,0.0002236162,0.004584404,0.0006602688,0.0229382],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004304768,"threshold_uncertainty_score":0.01290482,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05083150990347094,"score_gpt":0.1939885689867492,"score_spread":0.1431570590832783,"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."}}