{"id":"W2024562034","doi":"10.1145/1386352.1386402","title":"Content-based image retrieval via distributed databases","year":2008,"lang":"en","type":"article","venue":"","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Image retrieval; Information retrieval; Database; Content-based image retrieval; Automatic image annotation; Cluster analysis; The Internet; Focus (optics); Relevance (law); Server; Node (physics); Data mining; Image (mathematics); World Wide Web; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009440765,0.0005584554,0.001130798,0.001613874,0.0006109856,0.002240557,0.002221634,0.001325722,0.002403174],"category_scores_gemma":[0.003034466,0.000396001,0.0004368878,0.002975581,0.0006688661,0.00355036,0.001577168,0.0006958751,0.001282902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008680741,"about_ca_system_score_gemma":0.0005086326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002434743,"about_ca_topic_score_gemma":0.001320117,"domain_scores_codex":[0.9984002,0.0003283141,0.00008154751,0.0004035491,0.0007043481,0.00008210311],"domain_scores_gemma":[0.9987202,0.0004322087,0.0001001962,0.0004350132,0.0002708632,0.00004157559],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009915022,0.0006276182,0.002661992,0.0006968628,0.0002210333,0.001120241,0.0005530505,0.2235805,0.1286409,0.059095,0.01142973,0.5703814],"study_design_scores_gemma":[0.0001193795,0.0002905099,0.000978291,0.00002356999,0.00006777971,0.0008022834,0.0001775892,0.9286283,0.02760432,0.02773071,0.01353091,0.00004641748],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04601784,0.004257243,0.9398025,0.0004337602,0.0001126145,0.000264477,0.0001885408,0.002064741,0.006858255],"genre_scores_gemma":[0.7190582,0.002884011,0.2683735,0.0002794884,0.00033227,0.0002975255,0.0004833209,0.0001138296,0.008177919],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002434743,"threshold_uncertainty_score":0.008039415,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07557186992275289,"score_gpt":0.2750015577006636,"score_spread":0.1994296877779108,"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."}}