{"id":"W2163647143","doi":"10.1109/ism.2006.105","title":"MeTaMaF: Metadata Tagging and Mapping Framework for Managing Multimedia Content","year":2006,"lang":"en","type":"article","venue":"","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Metadata; Computer science; Metadata repository; Data element; Leverage (statistics); Meta Data Services; World Wide Web; Information retrieval; Geospatial metadata; Schema (genetic algorithms)","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":[0.003413543,0.0008063867,0.0009226574,0.003282874,0.001525794,0.002949885,0.003803157,0.001620357,0.002986511],"category_scores_gemma":[0.003822092,0.0005875044,0.00131629,0.001944746,0.001009323,0.006764082,0.003091177,0.001933236,0.00167448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001599802,"about_ca_system_score_gemma":0.002733632,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01213513,"about_ca_topic_score_gemma":0.01449277,"domain_scores_codex":[0.9988346,0.0002382199,0.0001580924,0.0001568303,0.0004838741,0.0001284114],"domain_scores_gemma":[0.99863,0.0003021802,0.0001350657,0.0004705316,0.0003074565,0.0001546319],"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":[0.0004230214,0.000584685,0.003030968,0.0007640343,0.0001586645,0.0006901411,0.001137713,0.02261075,0.04451567,0.1713501,0.06107684,0.6936573],"study_design_scores_gemma":[0.0001544688,0.0003930417,0.002193465,0.0002999674,0.0002179614,0.001705631,0.0007737926,0.463857,0.06705386,0.1335235,0.3294688,0.0003584331],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002784291,0.0002024882,0.9832349,0.0002364049,0.00004116713,0.0002453476,0.0003797422,0.01144852,0.001427184],"genre_scores_gemma":[0.03223329,0.000285879,0.9619906,0.0001835904,0.00004324611,0.0003471239,0.001545862,0.0004800489,0.002890287],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01213513,"threshold_uncertainty_score":0.02412897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06103266154089308,"score_gpt":0.2755470276223767,"score_spread":0.2145143660814836,"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."}}