{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003367924,0.000104006,0.0001433536,0.00009591651,0.0001273516,0.0003631657,0.0003780736,0.00004358487,0.000005730295],"category_scores_gemma":[0.00007148144,0.00008478206,0.00004974711,0.0001996755,0.00003689062,0.0007356027,0.0001575483,0.00007442271,0.000003905659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001690945,"about_ca_system_score_gemma":0.00001108639,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005963216,"about_ca_topic_score_gemma":0.000001808709,"domain_scores_codex":[0.9991153,0.00001986644,0.0002049415,0.0003175261,0.0001366897,0.0002056456],"domain_scores_gemma":[0.9992567,0.0002115714,0.00007816913,0.0003367045,0.00007391865,0.00004291015],"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":[0.000001512435,0.00001695073,0.00009660218,0.00002062534,0.00001351891,0.000001406959,0.00005104767,3.270829e-7,0.006400967,0.8897895,0.0004055553,0.1032021],"study_design_scores_gemma":[0.000537067,0.00005107683,0.003718408,0.00009625987,0.00003627046,0.00001723809,0.0002490686,0.3378101,0.2190298,0.375545,0.06232015,0.0005896371],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001397263,0.0004074125,0.9935327,0.003994461,0.00008847339,0.00026096,0.000002517813,0.00039101,0.001182701],"genre_scores_gemma":[0.07554099,0.0000311869,0.921939,0.0006367329,0.00005540651,0.00004195013,0.000005314274,0.000006981397,0.001742444],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5142444,"threshold_uncertainty_score":0.3502015,"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."}}