{"id":"W4248606973","doi":"10.1145/500934.500936","title":"Parallel traversal of signature trees for fast CBIR","year":2001,"lang":"en","type":"article","venue":"","topic":"Image Retrieval and Classification Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Tree traversal; Computer science; Signature (topology); Histogram; Binary tree; Tree (set theory); k-d tree; Image (mathematics); Parallel computing; Pattern recognition (psychology); Artificial intelligence; Algorithm; 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":[0.0000870181,0.00006118131,0.00008944745,0.00004394663,0.00003167023,0.00002598103,0.000408334,0.00005247389,0.00003012216],"category_scores_gemma":[0.00001402463,0.00004639286,0.00006604624,0.0001908408,0.00002854078,0.000178975,0.00003051286,0.00004056164,0.000005499559],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008353601,"about_ca_system_score_gemma":0.00002334848,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005389931,"about_ca_topic_score_gemma":0.000004813574,"domain_scores_codex":[0.9994877,0.00001011747,0.000126284,0.0001501343,0.0001129161,0.0001128489],"domain_scores_gemma":[0.9995691,0.00004424012,0.00004918821,0.0002175643,0.00008856379,0.00003131137],"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":[0.00005504591,0.000207924,0.0002407523,0.00002709894,0.00002426985,0.000003468437,0.0005037558,0.00001171057,0.06033525,0.5713133,0.01081425,0.3564631],"study_design_scores_gemma":[0.001320224,0.0007142288,0.005146996,0.000029793,0.000016002,0.00002442689,0.0002537394,0.1238103,0.7007136,0.04384717,0.1235966,0.0005268988],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0002700484,0.00004830866,0.9910209,0.001090678,0.00003922982,0.0001428896,0.000002008595,0.0001774438,0.007208482],"genre_scores_gemma":[0.7824547,0.00005001832,0.209082,0.0002545924,0.00003682687,0.00002224381,0.000003044911,0.000005316517,0.008091208],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7821847,"threshold_uncertainty_score":0.1891846,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01982974794356116,"score_gpt":0.2620619618518226,"score_spread":0.2422322139082615,"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."}}