{"id":"W2128207581","doi":"10.1109/cmpsac.1991.170198","title":"Dynamic spatial query language: a customized query language for object-oriented database systems","year":2002,"lang":"en","type":"article","venue":"","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Query language; Object Query Language; RDF query language; Data control language; Object (grammar); Query optimization; Query expansion; Query by Example; Spatial query; Information retrieval; Object-based spatial database; View; Sargable; Database; Spatial database; Programming language; Web search query; Database design; Web query classification; Spatial analysis; Artificial intelligence; Search engine","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000446711,0.0002439923,0.0003037237,0.0002267761,0.000138163,0.0003775561,0.001032595,0.00006060466,0.0001464672],"category_scores_gemma":[0.00009670524,0.0002076272,0.0001126818,0.0003909416,0.00003452924,0.001136261,0.0005065401,0.0001243757,0.0003148954],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006576397,"about_ca_system_score_gemma":0.00001985159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001714504,"about_ca_topic_score_gemma":0.0003239693,"domain_scores_codex":[0.9980801,0.00008842364,0.0003467645,0.0006344478,0.0003586232,0.0004916073],"domain_scores_gemma":[0.9983696,0.0001434952,0.0001270104,0.001177135,0.00005725977,0.000125529],"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":[0.0003016033,0.001915781,0.0002457607,0.001439617,0.000717277,0.001551371,0.01176165,0.0003382346,0.009821053,0.1324413,0.3627706,0.4766957],"study_design_scores_gemma":[0.002237972,0.00006295697,0.00004266026,0.0000458529,0.00002818225,0.00001284862,0.0009147604,0.9820316,0.0002621076,0.00001395597,0.01398041,0.0003666786],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005225112,0.0007088894,0.9851484,0.0003427837,0.001458319,0.0009331704,0.0002225112,0.0006931694,0.005267689],"genre_scores_gemma":[0.7138225,0.0001238267,0.1920404,0.001341744,0.0007304215,0.0005715662,0.001629171,0.0001008914,0.08963943],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9816934,"threshold_uncertainty_score":0.8466792,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0105628418730422,"score_gpt":0.2470393899691693,"score_spread":0.2364765480961271,"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."}}