{"id":"W2375735971","doi":"","title":"Semantic Search Strategy Of Heterogeneous Database Based On An Improved Particle Swarm Optimization","year":2009,"lang":"en","type":"article","venue":"Microcomputer applications","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Similarity (geometry); Particle swarm optimization; Ontology; Precision and recall; Semantic similarity; Data mining; Nearest neighbor search; Artificial intelligence; Information retrieval; Machine learning","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":[0.0001343668,0.0001428513,0.0001333648,0.000129879,0.0001367331,0.0001800328,0.000394571,0.0000464534,0.0000918041],"category_scores_gemma":[0.000001136191,0.0001374496,0.00004105125,0.0005219675,0.00004209992,0.0005323835,0.00006091149,0.0000813151,0.00008396599],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001331674,"about_ca_system_score_gemma":0.000023524,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008606503,"about_ca_topic_score_gemma":0.0000116398,"domain_scores_codex":[0.999014,0.000009407981,0.0002635769,0.0003537501,0.0001422619,0.0002170266],"domain_scores_gemma":[0.999157,0.00001816399,0.0001060818,0.0005018969,0.0001958314,0.00002107103],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000704015,0.001574695,0.0003250783,0.0001764702,0.00001395002,0.000002856983,0.00002457775,0.6822643,0.05736794,0.003830814,0.0004495598,0.2538993],"study_design_scores_gemma":[0.0002495812,0.00003537204,0.0006626884,0.00002426381,0.00002359181,0.000001775941,0.00001188753,0.9711905,0.02217183,0.0001483651,0.005302886,0.0001772874],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.051082,0.00002326772,0.9474146,0.0004077811,0.00001524029,0.0005883367,0.00002665665,0.000117726,0.0003243437],"genre_scores_gemma":[0.9721471,0.000004104398,0.02565167,0.001279197,0.0002910733,0.00004646957,0.0005494428,0.00001542376,0.00001552597],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9217629,"threshold_uncertainty_score":0.560503,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04510727776690166,"score_gpt":0.2959685310629077,"score_spread":0.2508612532960061,"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."}}