{"id":"W2112801673","doi":"10.1109/icassp.2004.1327291","title":"Practical MPEG-7 image indexing & retrieval for undergraduates","year":2004,"lang":"en","type":"article","venue":"","topic":"Video Analysis and Summarization","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Search engine indexing; Computer science; Multimedia; ASCII; Information retrieval; Set (abstract data type); Parsing; Index (typography); Image retrieval; Image (mathematics); Artificial intelligence; World Wide Web; Programming language","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":[0.0003415732,0.00008156001,0.0001138124,0.00007637368,0.0001371016,0.0002991949,0.000229262,0.00004850678,0.00001510822],"category_scores_gemma":[0.0004172424,0.00006722109,0.0000873035,0.0003865912,0.00002249362,0.0005874961,0.00008847781,0.00006894671,0.00006318613],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004941319,"about_ca_system_score_gemma":0.0001104304,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002771814,"about_ca_topic_score_gemma":0.00006164854,"domain_scores_codex":[0.9991031,0.00002370756,0.0001896316,0.0002728259,0.0002185871,0.0001921657],"domain_scores_gemma":[0.9993035,0.0001343404,0.0000612959,0.0002936622,0.000139192,0.00006805117],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.000009538328,0.00005903621,0.000163956,0.000007288677,0.00002742005,0.000003095764,0.0001223534,0.000292227,0.004249947,0.9920517,0.002011455,0.001001953],"study_design_scores_gemma":[0.002069889,0.0002143276,0.0009611887,0.0000317693,0.00007137597,0.00003796308,0.000100261,0.1555472,0.04188066,0.7772036,0.0212046,0.0006771189],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001466632,0.000008226135,0.9753051,0.02056815,0.00009515556,0.0001014375,5.62547e-7,0.0001148997,0.002339791],"genre_scores_gemma":[0.4357893,0.000006675751,0.5629208,0.0005258938,0.00005551516,0.000003165597,0.000009361754,0.000005637447,0.0006836323],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.4343227,"threshold_uncertainty_score":0.2885143,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04405913042278311,"score_gpt":0.3276901220365744,"score_spread":0.2836309916137913,"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."}}