{"id":"W1983996307","doi":"10.1109/cscwd.2014.6846921","title":"A study of intents resolving for service discovery","year":2014,"lang":"en","type":"article","venue":"","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Matching (statistics); Service discovery; Service (business); Similarity (geometry); Information retrieval; Order (exchange); Data science; Empirical research; World Wide Web; Web service; Data mining; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02067234,0.0008046197,0.001332124,0.004605857,0.003018782,0.004173505,0.003234555,0.002101059,0.003280291],"category_scores_gemma":[0.1233839,0.0005614209,0.001872245,0.007153713,0.00334634,0.0110065,0.002647717,0.003718644,0.0006153188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003693916,"about_ca_system_score_gemma":0.003045878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006031701,"about_ca_topic_score_gemma":0.003460436,"domain_scores_codex":[0.9821016,0.008168895,0.001443303,0.002654676,0.00489589,0.0007356305],"domain_scores_gemma":[0.8547275,0.1136107,0.008019946,0.01494299,0.006878618,0.001820169],"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":[0.001911213,0.001634345,0.06517176,0.001945419,0.000462759,0.0006544133,0.00371657,0.1000509,0.01090335,0.3342082,0.01544405,0.4638971],"study_design_scores_gemma":[0.0001410675,0.0009807945,0.01563454,0.0001639196,0.000176229,0.001352558,0.002553981,0.7479221,0.006847421,0.1986721,0.0254395,0.0001158748],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3625156,0.004173127,0.6089647,0.005600618,0.0003250038,0.001151463,0.003231729,0.0009261956,0.01311156],"genre_scores_gemma":[0.6780081,0.001177172,0.3125396,0.0004591757,0.0002497093,0.0003589663,0.004453377,0.0001479332,0.002605924],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02067234,"threshold_uncertainty_score":0.1093271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3462392937357613,"score_gpt":0.4645175144537989,"score_spread":0.1182782207180376,"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."}}