{"id":"W2490627700","doi":"10.4018/978-1-61350-126-9.ch010","title":"Towards a Dynamic Semantic and Complex Relationship Modeling of Multimedia Data","year":2013,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Alphanumeric; Metadata; Semantics (computer science); Multimedia; Information retrieval; Semantic data model; Perspective (graphical); World Wide Web; Data model (GIS); Artificial intelligence; 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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001875821,0.0002606789,0.0003567738,0.00008369276,0.00007547713,0.0001169451,0.001332831,0.0002499322,0.00001233589],"category_scores_gemma":[0.00004964899,0.0002456755,0.00006508423,0.00003199249,0.0001333189,0.0002092034,0.0009169203,0.0002166176,0.00004905985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000750855,"about_ca_system_score_gemma":0.0001659147,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001082077,"about_ca_topic_score_gemma":0.0000135841,"domain_scores_codex":[0.9983917,0.00002249349,0.0004567535,0.0005794633,0.0003658804,0.0001836871],"domain_scores_gemma":[0.997981,0.00004911416,0.0002629517,0.001407639,0.0001981241,0.0001012028],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002702685,0.000005990309,0.000006094602,0.0000640379,0.00002466253,0.000003493741,0.0000389534,0.00000164715,0.00004888462,0.9422507,0.0002548627,0.05729798],"study_design_scores_gemma":[0.00009915137,0.00002302232,0.000110554,0.0001195778,0.00002703556,0.00001896671,0.000002469427,0.6493662,0.00001359532,0.3493265,0.0006886428,0.0002043002],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00001450366,0.0003014132,0.6086627,0.0001320261,0.00008516762,0.0003083529,0.0001029498,0.0001959044,0.3901969],"genre_scores_gemma":[0.7636832,0.00004649819,0.2166035,0.0001390645,0.00005013157,0.00001257785,0.00006638832,0.00003330341,0.0193653],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7636687,"threshold_uncertainty_score":0.9999995,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08527768874488137,"score_gpt":0.3015419134346423,"score_spread":0.2162642246897609,"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."}}