{"id":"W2355085396","doi":"","title":"Research of Indexing for Moving Object","year":2006,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Search engine indexing; Quadtree; Computer science; Variation (astronomy); Object (grammar); Index (typography); R-tree; Tree (set theory); Data mining; Artificial intelligence; Spatial database; Spatial analysis; Mathematics; Statistics; World Wide Web","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004783279,0.00007256927,0.00009757443,0.0002339708,0.0002021744,0.0001593522,0.001128886,0.00002910351,0.000001856171],"category_scores_gemma":[5.445935e-7,0.00007472297,0.00005061103,0.0006642869,0.000044784,0.000284696,0.0004949946,0.00007831125,0.0000236475],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002438647,"about_ca_system_score_gemma":0.00002900289,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006288443,"about_ca_topic_score_gemma":0.0000065201,"domain_scores_codex":[0.9990115,0.00002314782,0.0002162942,0.0003302445,0.0001673994,0.0002514702],"domain_scores_gemma":[0.9991347,0.0001469046,0.0000611306,0.0004703839,0.0001618052,0.00002503498],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001174689,0.000153779,0.000169834,0.00006470704,0.0000138915,4.485497e-7,0.00008965165,0.0002059466,0.008282504,0.552749,0.02032746,0.4179416],"study_design_scores_gemma":[0.0003643354,0.00003517244,0.001928332,0.00002006015,0.000005117135,0.000002463755,0.00002145659,0.04314879,0.01455164,0.04962304,0.890117,0.0001825398],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0005544915,0.0000706667,0.9954743,0.0003458804,0.0000153781,0.0007002449,0.00001173503,0.00009072165,0.002736559],"genre_scores_gemma":[0.04371492,0.000002971714,0.9548036,0.00006071211,0.0002361564,0.0004708297,0.00004271488,0.000009232516,0.0006588506],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8697896,"threshold_uncertainty_score":0.3047114,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03385811878790541,"score_gpt":0.3266502604672358,"score_spread":0.2927921416793304,"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."}}