{"id":"W2137587644","doi":"10.1109/tmm.2003.813280","title":"Joint semantics and feature based image retrieval using relevance feedback","year":2003,"lang":"en","type":"article","venue":"IEEE Transactions on Multimedia","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Relevance feedback; Computer science; Image retrieval; Relevance (law); Semantics (computer science); Information retrieval; Ranking (information retrieval); Feature (linguistics); Image (mathematics); Automatic image annotation; Artificial intelligence; Data mining; Pattern recognition (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":[],"consensus_categories":[],"category_scores_codex":[0.0002622013,0.0002010267,0.0001902602,0.0001595219,0.0002385038,0.0001419154,0.0002234011,0.0001438252,0.00002683586],"category_scores_gemma":[0.00005499505,0.0001887547,0.00009050887,0.0005405498,0.0001338192,0.0004062314,0.000001858127,0.000370227,0.00003352124],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000779324,"about_ca_system_score_gemma":0.0001043292,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004874276,"about_ca_topic_score_gemma":0.000001168153,"domain_scores_codex":[0.9986675,0.00010768,0.0002155597,0.0004291922,0.0003118342,0.0002682664],"domain_scores_gemma":[0.9989589,0.0001570146,0.00009279668,0.0004943032,0.0001567929,0.0001401419],"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":[0.00005280693,0.0003322691,0.00001335738,0.0000793081,0.00003081255,0.00002968143,0.0003468886,0.0001875504,0.9757559,0.0004636204,0.0001688008,0.02253898],"study_design_scores_gemma":[0.0004136321,0.00005901924,0.00007781735,0.0000406918,0.00001608985,0.00002412917,0.00001432832,0.1625234,0.8356081,0.0001753612,0.0008424262,0.0002050666],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002873174,0.00007887148,0.9952294,0.0007273142,0.0004132231,0.0002424383,0.0000119976,0.0003097005,0.0001139437],"genre_scores_gemma":[0.3458388,0.00009339411,0.6533558,0.000249411,0.00002139442,0.000004210309,9.662501e-7,0.00002037213,0.000415587],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3429657,"threshold_uncertainty_score":0.7697192,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02672601995115716,"score_gpt":0.2609262115134166,"score_spread":0.2342001915622594,"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."}}