{"id":"W7043032612","doi":"","title":"Similarity search and applications 5th international conference, SISAP 2012, Toronto, ON, Canada, August 9 - 10, 2012 ; proceedings","year":2012,"lang":"en","type":"article","venue":"","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Similarity (geometry); Similitude; Feature (linguistics); Nearest neighbor search; Search engine indexing","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004574084,0.001353308,0.002900178,0.003891306,0.002106495,0.005792179,0.003060474,0.001494597,0.03846826],"category_scores_gemma":[0.005491829,0.0006377401,0.001551596,0.005561781,0.001630799,0.003134235,0.003404008,0.002204832,0.01611612],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004039048,"about_ca_system_score_gemma":0.01018563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06461424,"about_ca_topic_score_gemma":0.09162735,"domain_scores_codex":[0.9976267,0.0004391472,0.0002173715,0.0002944947,0.001169007,0.0002532017],"domain_scores_gemma":[0.9947812,0.0004456633,0.00007805758,0.0007773588,0.003333033,0.0005847171],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003340648,0.0003269851,0.001463806,0.0004872263,0.0001552065,0.0001214568,0.0002457573,0.00213881,0.005085151,0.009682458,0.4563612,0.523598],"study_design_scores_gemma":[0.0001004294,0.0003558347,0.007410909,0.0004360659,0.0002159684,0.000738367,0.0009190266,0.06523145,0.01302082,0.0273365,0.8841123,0.000122308],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.0411293,0.1043124,0.7042744,0.016127,0.02817675,0.001440926,0.01009668,0.01942075,0.07502184],"genre_scores_gemma":[0.09403466,0.04276714,0.4821906,0.001854277,0.003251274,0.0006500499,0.03764898,0.002552683,0.3350504],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.06461424,"threshold_uncertainty_score":0.1286892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03367659756730555,"score_gpt":0.2807233317473065,"score_spread":0.2470467341800009,"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."}}