{"id":"W2155371281","doi":"10.5194/isprsarchives-xxxix-b2-167-2012","title":"NON-SPATIAL AND GEOSPATIAL SEMANTIC QUERY OF HEALTH INFORMATION","year":2012,"lang":"en","type":"article","venue":"The international archives of the photogrammetry, remote sensing and spatial information sciences/International archives of the photogrammetry, remote sensing and spatial information sciences","topic":"Semantic Web and Ontologies","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Fredericton; University of New Brunswick","funders":"","keywords":"Geospatial analysis; Computer science; Information retrieval; Spatial analysis; Data science; Geography; Cartography; Remote sensing","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":[0.003616008,0.0003880548,0.000700651,0.002388428,0.0008257995,0.003533972,0.0009131352,0.001033091,0.003320732],"category_scores_gemma":[0.006866623,0.0002315967,0.0008541616,0.002891403,0.001189704,0.005021688,0.002427458,0.0006124612,0.0006361963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001398176,"about_ca_system_score_gemma":0.001579635,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006563366,"about_ca_topic_score_gemma":0.007779527,"domain_scores_codex":[0.9958063,0.001488968,0.0005465598,0.0003985298,0.001592749,0.0001669125],"domain_scores_gemma":[0.9969509,0.001543178,0.0002587319,0.0004691432,0.0006633455,0.0001146643],"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":[0.0008550496,0.0005160368,0.01227913,0.001557664,0.0003549369,0.001790886,0.002776191,0.05233087,0.02334813,0.6276165,0.0304246,0.2461499],"study_design_scores_gemma":[0.0001201213,0.0001839884,0.00481731,0.0002639272,0.0002114371,0.001050422,0.002600256,0.5770617,0.02073652,0.3024928,0.09038488,0.00007679839],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08837827,0.001757971,0.8675863,0.005438665,0.00023619,0.0007102021,0.003535622,0.002931069,0.02942567],"genre_scores_gemma":[0.7224111,0.001155467,0.2653731,0.0009248889,0.0001114445,0.0002593938,0.003937856,0.0001351786,0.005691604],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006563366,"threshold_uncertainty_score":0.01912349,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01993689352131545,"score_gpt":0.2642681329208013,"score_spread":0.2443312393994858,"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."}}