{"id":"W2034485749","doi":"10.1007/s10115-008-0190-y","title":"Effectiveness of NAQ-tree as index structure for similarity search in high-dimensional metric space","year":2009,"lang":"en","type":"article","venue":"Knowledge and Information Systems","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Nearest neighbor search; Metric space; Tree (set theory); Tree traversal; Mathematics; Computer science; Cover tree; Data mining; Metric (unit); Disjoint sets; Algorithm; Pattern recognition (psychology); Artificial intelligence; Combinatorics; Cluster analysis; Discrete mathematics","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":[0.0007234361,0.0001131885,0.0002517542,0.0004620289,0.00006113452,0.00007719929,0.0002179976,0.0001049853,7.546592e-7],"category_scores_gemma":[0.0001431662,0.00009503032,0.00003355059,0.0008389863,0.00002281652,0.002571238,0.00007239063,0.0001158129,0.000003697807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006019512,"about_ca_system_score_gemma":0.00007797482,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000376219,"about_ca_topic_score_gemma":0.000002076478,"domain_scores_codex":[0.9990692,0.0001003961,0.0003301882,0.0001360678,0.0002012671,0.000162857],"domain_scores_gemma":[0.9989765,0.0002504324,0.0001160887,0.0002019257,0.0004024836,0.00005260393],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005094546,0.0002282216,0.006363624,0.003654141,0.00005457967,0.000004044006,0.003579268,0.00182877,0.007844221,0.5575461,0.00106366,0.4173239],"study_design_scores_gemma":[0.00672451,0.002742149,0.2784071,0.001529469,0.00002114149,0.00009373822,0.0002687488,0.2778988,0.3840469,0.03086307,0.01631086,0.001093525],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09559017,0.0009380045,0.9006771,0.00005010457,0.0002015963,0.0009534939,0.00001708833,0.0000826312,0.001489792],"genre_scores_gemma":[0.9971531,0.00002033735,0.002725569,0.00002648383,0.00002115915,0.00001324823,0.00001382745,0.000002505238,0.00002375717],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9015629,"threshold_uncertainty_score":0.3875224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009903275750799953,"score_gpt":0.2899844482842681,"score_spread":0.2800811725334681,"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."}}