{"id":"W2496229158","doi":"10.4018/978-1-4666-0330-1.ch016","title":"Context-Aware Mobile Search Engine","year":2012,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lakehead University","funders":"","keywords":"Computer science; World Wide Web; Context (archaeology); Mobile Web; Usability; Search analytics; The Internet; Context awareness; Mobile device; Search engine; Human–computer interaction; Mobile technology; Web search query","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":[0.0002244859,0.0004178476,0.0004605892,0.0007533941,0.0004575928,0.001592121,0.0007078103,0.0009977606,0.002794729],"category_scores_gemma":[0.0006669746,0.0002481854,0.0003613433,0.0007916904,0.0002364902,0.002047786,0.0008798817,0.000510839,0.001380472],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004347969,"about_ca_system_score_gemma":0.0004261575,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002682312,"about_ca_topic_score_gemma":0.004724296,"domain_scores_codex":[0.9998086,0.00004065028,0.00001368385,0.00003541532,0.00007354197,0.0000281493],"domain_scores_gemma":[0.9998611,0.00004144196,0.000009668003,0.00002248515,0.0000505091,0.00001474817],"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":[0.0006722682,0.00038022,0.003907738,0.001788475,0.0001736364,0.002310209,0.002315234,0.02034226,0.09397965,0.1105127,0.03489928,0.7287184],"study_design_scores_gemma":[0.000141004,0.0003968862,0.009686269,0.0006292425,0.0005204171,0.006926223,0.002172901,0.3890009,0.05712759,0.05767268,0.4755054,0.0002205813],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2120738,0.03011378,0.5329863,0.001897458,0.0004906293,0.0006682726,0.0009732804,0.009672124,0.2111245],"genre_scores_gemma":[0.7729582,0.006544751,0.1743429,0.0004271879,0.00009594606,0.0001796066,0.0007811608,0.0001978242,0.04447249],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002794729,"threshold_uncertainty_score":0.009349346,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02944570427739806,"score_gpt":0.2632839360912232,"score_spread":0.2338382318138251,"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."}}