{"id":"W1583755464","doi":"10.1007/978-3-540-72685-2_31","title":"Visualization of GML Map Using 3-Layer POI on Mobile Device","year":2007,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Mobile and Web Applications","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"St. Francis Xavier University","funders":"","keywords":"Computer science; Shapefile; Visualization; Interoperability; Geographic information system; Flexibility (engineering); Information retrieval; Mobile device; Database; Spatial analysis; Data mining; Distributed GIS; GIS file format; Data visualization; Layer (electronics); World Wide Web; GIS applications; AM/FM/GIS; Metadata; Cartography; Geography","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":[0.00008896098,0.0007487208,0.0002918112,0.00132348,0.0003629044,0.0008103452,0.0003723437,0.0004573713,0.02339646],"category_scores_gemma":[0.0002836204,0.000197864,0.000394648,0.000905198,0.0001767893,0.000474931,0.0006001259,0.0005643422,0.001867327],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002298201,"about_ca_system_score_gemma":0.0005274882,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005273099,"about_ca_topic_score_gemma":0.005933808,"domain_scores_codex":[0.9999415,0.000006229282,0.000001986553,0.000009105797,0.00002364386,0.00001760659],"domain_scores_gemma":[0.9998807,0.00002377771,0.000008693273,0.00001842995,0.00004362239,0.00002481566],"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":[0.002101432,0.0005232577,0.009237884,0.001816596,0.0001220754,0.003052144,0.003922304,0.06382201,0.2055025,0.01754251,0.1899011,0.5024561],"study_design_scores_gemma":[0.0004478464,0.0003896345,0.0487982,0.0005653982,0.0002429642,0.001384407,0.002757478,0.4900341,0.1375701,0.01327273,0.3040754,0.0004618194],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2798451,0.0007513929,0.4465175,0.002755493,0.001627187,0.0005681626,0.02121129,0.1070524,0.1396715],"genre_scores_gemma":[0.7370805,0.0006742805,0.2182465,0.0003931686,0.0001907776,0.000337334,0.006973125,0.004471049,0.03163329],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02339646,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03927944882282318,"score_gpt":0.3168686500149714,"score_spread":0.2775892011921482,"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."}}