{"id":"W4240645821","doi":"10.4018/978-1-59904-002-8.ch062","title":"Knowledge Representation in Semantic Mobile Applications","year":2007,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Semantic Web; Representation (politics); Data science; Knowledge representation and reasoning; World Wide Web; Social Semantic Web; Knowledge management; Information retrieval; Artificial intelligence; Political science","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":[0.001647967,0.0008722853,0.0005956042,0.002719966,0.001205056,0.007319195,0.002293286,0.002568769,0.006444593],"category_scores_gemma":[0.002215855,0.0005544791,0.0009652094,0.005985423,0.002900567,0.01042627,0.002939225,0.002276449,0.00282098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00235179,"about_ca_system_score_gemma":0.001342777,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003581024,"about_ca_topic_score_gemma":0.003160718,"domain_scores_codex":[0.9988229,0.0004841024,0.0001006113,0.0001586202,0.0003329802,0.000100769],"domain_scores_gemma":[0.9995309,0.0002643916,0.00002083981,0.00009960964,0.0000601324,0.00002403032],"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":[0.000006889288,0.00001610985,0.00005422391,0.0002362779,0.00001138977,0.0001752109,0.0006564035,0.002830358,0.0004692131,0.9123279,0.00825638,0.07495958],"study_design_scores_gemma":[0.000005135976,0.000009024627,0.0001109551,0.0004153944,0.00001877247,0.0003287235,0.0004156585,0.01451828,0.0009712873,0.6626787,0.3205117,0.00001641659],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004795513,0.02936951,0.7803044,0.006761219,0.0007395917,0.0001888355,0.0004263367,0.001276861,0.1761378],"genre_scores_gemma":[0.1948818,0.05011875,0.6523618,0.002996534,0.0010096,0.0007206971,0.002739922,0.0005979646,0.09457294],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.007319195,"threshold_uncertainty_score":0.02155936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0426970131509978,"score_gpt":0.3204786193888143,"score_spread":0.2777816062378166,"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."}}