{"id":"W2092556275","doi":"10.1145/1557626.1557659","title":"Use of semantic web technology for adding 3D detail to GIS landscape data","year":2009,"lang":"en","type":"article","venue":"","topic":"3D Modeling in Geospatial Applications","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Visualization; Ontology; Semantic Web; Geographic information system; Fidelity; Semantics (computer science); Information retrieval; World Wide Web; Data mining; Remote sensing; 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":[0.003622911,0.0008742186,0.0007630796,0.006660506,0.001029878,0.004036103,0.00161267,0.001386723,0.002511991],"category_scores_gemma":[0.006247431,0.000793565,0.002136134,0.006032939,0.002274284,0.009554218,0.003995067,0.002460253,0.0010824],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001156364,"about_ca_system_score_gemma":0.001446285,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004380487,"about_ca_topic_score_gemma":0.005557812,"domain_scores_codex":[0.9972948,0.0007162951,0.0003675315,0.0002883248,0.001252557,0.00008041914],"domain_scores_gemma":[0.9949417,0.002038453,0.0003617615,0.001880429,0.000652708,0.0001250389],"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":[0.0001164112,0.000213159,0.002881843,0.001746067,0.0003599547,0.001463631,0.003176749,0.01696327,0.02050555,0.5303738,0.01425501,0.4079446],"study_design_scores_gemma":[0.00004706452,0.00008252411,0.00248116,0.0008757632,0.0002499779,0.001446589,0.000900218,0.06737934,0.02339432,0.3768643,0.5260783,0.0002004502],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003761913,0.0006276973,0.9826925,0.0007180284,0.0001363031,0.0001048691,0.0005996537,0.002589806,0.008769297],"genre_scores_gemma":[0.07015494,0.003073688,0.9177485,0.0005627184,0.0001451511,0.0002275162,0.003621202,0.0006462824,0.003820126],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006660506,"threshold_uncertainty_score":0.01915997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04666216461603243,"score_gpt":0.2678063126164486,"score_spread":0.2211441480004162,"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."}}