{"id":"W2543408643","doi":"10.1109/iat.2005.50","title":"Category-based Similarity Algorithm for Semantic Similarity in Multi-agent Information Sharing Systems","year":2006,"lang":"en","type":"article","venue":"IEEE/WIC/ACM International Conference on Intelligent Agent Technology","topic":"Topic Modeling","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Semantic similarity; Similarity (geometry); Computer science; Cosine similarity; Information retrieval; Vector space model; Matching (statistics); Similarity measure; Data mining; Artificial intelligence; Pattern recognition (psychology); Mathematics; Image (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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006717884,0.0004170787,0.0004263881,0.001398852,0.000158122,0.0004204674,0.003261983,0.0004362519,0.00003808046],"category_scores_gemma":[0.0002258593,0.0004371981,0.0001561642,0.0004971981,0.0001121827,0.0006612898,0.0004877788,0.0005889072,0.0001217523],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000710124,"about_ca_system_score_gemma":0.0002005915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008478803,"about_ca_topic_score_gemma":0.0002883064,"domain_scores_codex":[0.9966378,0.00005974346,0.001171241,0.0008520071,0.0006458498,0.0006333406],"domain_scores_gemma":[0.9974876,0.0001330253,0.0004333453,0.001171958,0.0006854839,0.00008860164],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005129804,0.0009657656,0.006443074,0.000174323,0.0001155862,0.000072483,0.0004095649,0.08287194,0.001125031,0.7952481,0.0007997552,0.1117231],"study_design_scores_gemma":[0.0007844201,0.0001169542,0.0004046345,0.0001494625,0.00001034529,0.00001274767,0.0001402115,0.9664533,0.008683668,0.01980291,0.003027144,0.0004141634],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01652383,0.00005366909,0.9744409,0.003772787,0.002908374,0.001089319,0.00005269534,0.000528071,0.0006303509],"genre_scores_gemma":[0.9357647,0.00003143139,0.0629486,0.0003916972,0.0001048379,0.0004133508,0.0001112561,0.00002005903,0.0002140866],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9192408,"threshold_uncertainty_score":0.999808,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08304876257932589,"score_gpt":0.3153846540817681,"score_spread":0.2323358915024422,"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."}}