{"id":"W2971000368","doi":"10.14778/3352063.3352080","title":"VISE","year":2019,"lang":"en","type":"article","venue":"Proceedings of the VLDB Endowment","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Pipeline (software); Interface (matter); Convolutional neural network; Nearest neighbor search; Scalability; Feature (linguistics); Image retrieval; Artificial intelligence; Frame (networking); Search engine; Computer vision; Information retrieval; Image (mathematics); Database","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":[0.0001567851,0.00008857049,0.0001166967,0.00004284029,0.00003779263,0.00004511046,0.001084499,0.00002426076,0.00001351337],"category_scores_gemma":[0.00003756264,0.00005642055,0.00007858957,0.0002968841,0.00002655009,0.0004795687,0.0005483428,0.00008570979,0.00003314406],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003460358,"about_ca_system_score_gemma":0.0000131879,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004417752,"about_ca_topic_score_gemma":5.083884e-8,"domain_scores_codex":[0.9992056,0.000002219617,0.0001546125,0.0002042739,0.000268277,0.0001650531],"domain_scores_gemma":[0.9994925,0.00001675849,0.0001352673,0.0002041806,0.0001190622,0.00003218862],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00002105681,0.0001423019,0.009712984,0.0001413692,0.00003024902,5.209541e-7,0.0006219401,0.000003788893,0.5416403,0.3761461,0.005878652,0.06566069],"study_design_scores_gemma":[0.0001686293,0.00009203671,0.001174668,0.0000517929,0.000003401258,0.000005635633,0.00002269149,0.0002559251,0.958964,0.02490419,0.01426837,0.00008861961],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.571269,0.001142027,0.1623323,0.008188185,0.001716741,0.003857265,0.000005872852,0.001459518,0.2500291],"genre_scores_gemma":[0.9698362,0.00004561763,0.02831756,0.0002980476,0.00002197359,0.00001519666,6.140412e-8,0.00000665575,0.001458678],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4173237,"threshold_uncertainty_score":0.2300763,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005005524439825163,"score_gpt":0.2170886034700969,"score_spread":0.2120830790302718,"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."}}