{"id":"W2944790191","doi":"10.48550/arxiv.1905.02009","title":"Visually-aware Recommendation with Aesthetic Features","year":2019,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Visual Attention and Saliency Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"National Natural Science Foundation of China","keywords":"Computer science; Recommender system; Pairwise comparison; Clothing; Key (lock); Perception; Human–computer interaction; Product (mathematics); Artificial intelligence; Space (punctuation); Information retrieval; Process (computing); Dynamics (music); Machine learning; Mathematics; Psychology","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":[0.000162889,0.0002657522,0.0002297622,0.0002698207,0.0001484449,0.0001827573,0.0008867726,0.0002313999,0.00005832824],"category_scores_gemma":[0.000004972251,0.0002613564,0.0001337754,0.0004906737,0.00004621398,0.0004294502,0.0006640244,0.0004964869,0.0002270179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001683537,"about_ca_system_score_gemma":0.0001233063,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007289866,"about_ca_topic_score_gemma":0.00005325757,"domain_scores_codex":[0.9984015,0.0001509171,0.000141301,0.0009543131,0.0001008483,0.0002511808],"domain_scores_gemma":[0.9987083,0.00002249685,0.000232006,0.0007637303,0.0001690712,0.0001044117],"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":[0.0005132399,0.001361568,0.01611917,0.0007020106,0.0004459605,0.000610906,0.002014857,0.5090322,0.0002143458,0.3808683,0.008517888,0.07959953],"study_design_scores_gemma":[0.001672931,0.0007818926,0.01155505,0.0003063336,0.00012067,0.00009538827,0.0002980368,0.9634796,0.000411255,0.01486975,0.00496055,0.001448508],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1553837,0.00001035046,0.8397861,0.0004104335,0.00081104,0.0003287115,0.000005658368,0.0003696169,0.002894433],"genre_scores_gemma":[0.9951294,0.00005033505,0.0004497822,0.0001812364,0.00003128979,0.000001236357,0.00004126603,0.00001690073,0.004098566],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8397456,"threshold_uncertainty_score":0.9999838,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0532979500067744,"score_gpt":0.2031261704562826,"score_spread":0.1498282204495082,"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."}}