{"id":"W2490474310","doi":"10.1016/j.procs.2016.08.026","title":"Mining Collective Opinions for Comparison of Mobile Apps","year":2016,"lang":"en","type":"article","venue":"Procedia Computer Science","topic":"Digital Marketing and Social Media","field":"Social Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Acadia University","funders":"","keywords":"Computer science; Mobile apps; Purchasing; World Wide Web; Product (mathematics); Sentiment analysis; Order (exchange); Revenue; Download; App store; Key (lock); Preference; Internet privacy; Artificial intelligence; Computer security","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":[0.002885214,0.001194161,0.001272082,0.01054544,0.0008897578,0.001757367,0.0009875135,0.001260162,0.001716777],"category_scores_gemma":[0.0139587,0.0002621511,0.001430629,0.005203653,0.0003878821,0.001842614,0.0008632928,0.000798784,0.001096297],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007136416,"about_ca_system_score_gemma":0.0006050426,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002060551,"about_ca_topic_score_gemma":0.003245126,"domain_scores_codex":[0.9958375,0.0007786623,0.0006504307,0.00110226,0.001362414,0.0002687082],"domain_scores_gemma":[0.9917045,0.004054284,0.001353878,0.0005150913,0.002116595,0.0002557209],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001380987,0.0009557402,0.1363326,0.001427673,0.001362199,0.001362931,0.001947084,0.0140086,0.03500667,0.003314339,0.02023056,0.7826707],"study_design_scores_gemma":[0.0001315625,0.001166444,0.182054,0.0002160929,0.0009709798,0.001585456,0.003596136,0.7521701,0.01926919,0.01342025,0.02524789,0.0001718199],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7217963,0.003826399,0.2448071,0.001168385,0.0005796221,0.001171719,0.01136733,0.002303877,0.01297936],"genre_scores_gemma":[0.9017975,0.0004398651,0.08588024,0.0001113764,0.0004133593,0.0005036602,0.008845423,0.00006344198,0.00194518],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01054544,"threshold_uncertainty_score":0.01525861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03576990009422392,"score_gpt":0.3510896713947813,"score_spread":0.3153197713005574,"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."}}