{"id":"W2076486399","doi":"10.3166/isi.15.1.35-60","title":"Stratégies alternatives pour la recherche des plus proches voisins dans les espaces multidimensionnels","year":2010,"lang":"fr","type":"article","venue":"Ingénierie des systèmes d information","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Curse of dimensionality; Nearest neighbor search; Dimension (graph theory); Computer science; Probabilistic logic; Similarity (geometry); Mathematics; Theoretical computer science; Data mining; Artificial intelligence; Combinatorics","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":["metaepi_narrow","scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.002370882,0.0004480408,0.0003391646,0.0003393678,0.0006826747,0.002595255,0.00112972,0.0004164602,0.00005651361],"category_scores_gemma":[0.001932374,0.0004266785,0.0001261983,0.0006828275,0.00103243,0.01691093,0.000590259,0.0008010306,0.000271502],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000380921,"about_ca_system_score_gemma":0.0003676656,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001514926,"about_ca_topic_score_gemma":0.000814176,"domain_scores_codex":[0.9972488,0.0005200687,0.0007464013,0.0003632224,0.0004931369,0.0006283346],"domain_scores_gemma":[0.9972982,0.0008090899,0.0005387883,0.0006104619,0.0005718042,0.0001716389],"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":[0.00002259576,0.0001118567,0.001299471,0.0009302524,0.0001324934,0.00002111274,0.1280282,0.0007520727,0.002801168,0.1167413,0.001184648,0.7479748],"study_design_scores_gemma":[0.002374738,0.0004006582,0.0362453,0.002277414,0.0001710228,0.0003308681,0.05179142,0.6563116,0.04247742,0.1090287,0.09652032,0.002070488],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3519568,0.0007035669,0.6197367,0.001515247,0.001571424,0.000573123,0.0000948389,0.000394639,0.02345364],"genre_scores_gemma":[0.6033888,0.0007102647,0.3884817,0.0001033282,0.0003219948,0.00007846543,0.0001086559,0.00003044799,0.006776335],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7459043,"threshold_uncertainty_score":0.9998185,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1241779971826965,"score_gpt":0.3132868043507056,"score_spread":0.1891088071680092,"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."}}