{"id":"W2024678590","doi":"10.1145/602421.602453","title":"Use of the SAND spatial browser for digital government applications","year":2003,"lang":"en","type":"article","venue":"Communications of the ACM","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":80,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Interface (matter); Spatial analysis; World Wide Web; The Internet; Information retrieval; Web browser; Spatial data infrastructure; Agency (philosophy); 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":[0.001274924,0.0008224365,0.0006141008,0.002378087,0.001048128,0.002848247,0.001316494,0.0006926853,0.03429292],"category_scores_gemma":[0.006344968,0.000630008,0.0005879455,0.002271365,0.00057251,0.003980461,0.003218521,0.0007507932,0.01370687],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001166935,"about_ca_system_score_gemma":0.002399675,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01486314,"about_ca_topic_score_gemma":0.02726689,"domain_scores_codex":[0.9988525,0.0002398223,0.000143229,0.0001435637,0.0004977111,0.0001231206],"domain_scores_gemma":[0.9969698,0.001044764,0.0001070123,0.0007759066,0.0008760102,0.0002265869],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00099328,0.0002137819,0.006085733,0.0006103533,0.000115536,0.001564716,0.002546755,0.005225084,0.01409286,0.09889624,0.5719946,0.297661],"study_design_scores_gemma":[0.0001002552,0.00003084302,0.001176901,0.0001676836,0.0000562418,0.0006617409,0.0005599404,0.03212089,0.01560975,0.02151167,0.9279183,0.00008582085],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01902046,0.0005950134,0.5042453,0.001298211,0.0002838938,0.0005847484,0.008678502,0.3223422,0.1429517],"genre_scores_gemma":[0.2853117,0.001840712,0.5691838,0.001166941,0.0002018951,0.001506085,0.02050824,0.02098804,0.09929264],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03429292,"threshold_uncertainty_score":0.1147212,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06115913605671689,"score_gpt":0.2656214992029471,"score_spread":0.2044623631462302,"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."}}