{"id":"W1589062066","doi":"10.1109/icws.2015.30","title":"Extracting, Ranking, and Evaluating Quality Features of Web Services through User Review Sentiment Analysis","year":2015,"lang":"en","type":"article","venue":"","topic":"Service-Oriented Architecture and Web Services","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Ranking (information retrieval); Quality (philosophy); Sentiment analysis; Information retrieval; World Wide Web; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001934705,0.000229864,0.0005585063,0.0001371751,0.0001010061,0.0001254273,0.0008231907,0.00006345253,0.00005412353],"category_scores_gemma":[0.00002517053,0.0001710023,0.0001675463,0.001387582,0.0000288609,0.0006755342,0.0005180186,0.0001508754,0.000008057584],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001795408,"about_ca_system_score_gemma":0.00007334326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002294122,"about_ca_topic_score_gemma":0.001552841,"domain_scores_codex":[0.9973227,0.0003884936,0.0005926664,0.0005748635,0.0008430805,0.0002781346],"domain_scores_gemma":[0.9979425,0.0002124821,0.0004900721,0.0008562286,0.0003651895,0.0001335486],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003337203,0.002125335,0.3515272,0.03433126,0.01234293,0.00007025312,0.1702217,0.00372227,0.02854686,0.1685622,0.0064054,0.2218108],"study_design_scores_gemma":[0.01683291,0.002553101,0.3674281,0.015866,0.01698407,0.0003319846,0.0226855,0.2326414,0.08410936,0.04532986,0.1865211,0.008716581],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8281233,0.07882123,0.04670099,0.007343894,0.000559847,0.00111156,0.00001388765,0.0005243766,0.03680089],"genre_scores_gemma":[0.8720265,0.001314134,0.1155362,0.01051388,0.00009873464,0.00002477907,0.00002211975,0.00001772399,0.0004460016],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2289192,"threshold_uncertainty_score":0.6973271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04974594866229595,"score_gpt":0.3753971554552797,"score_spread":0.3256512067929838,"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."}}