{"id":"W2972128553","doi":"10.22215/etd/2019-13484","title":"Persuasive Content Generator The Design, Development and Validation of Persuasive Contect Generator Based on Social Media Profiles","year":2019,"lang":"en","type":"dissertation","venue":"","topic":"Advanced Text Analysis Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Popularity; Categorization; Social media; Comprehension; Internet privacy; Persuasion; World Wide Web; The Internet; Generator (circuit theory); Psychology; Social psychology; Power (physics); 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":[0.01629866,0.001194194,0.0008515729,0.003178012,0.0008772133,0.002942937,0.002221226,0.001473747,0.005051651],"category_scores_gemma":[0.06227513,0.0008956006,0.0006108782,0.0009356252,0.001303429,0.004510857,0.002435861,0.001458601,0.002583568],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001066183,"about_ca_system_score_gemma":0.001621487,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004598485,"about_ca_topic_score_gemma":0.0004021838,"domain_scores_codex":[0.9914773,0.004522371,0.0007526826,0.001084916,0.001938166,0.0002246078],"domain_scores_gemma":[0.9448035,0.03716975,0.001982473,0.005336419,0.009725976,0.0009818542],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00339499,0.004124936,0.01822246,0.001981806,0.0002151933,0.0007859519,0.01372714,0.01193272,0.06535889,0.04109947,0.007909065,0.8312473],"study_design_scores_gemma":[0.002035171,0.006571565,0.01718372,0.0007274452,0.0004836937,0.001265038,0.003750306,0.6183553,0.2253938,0.04324862,0.08059192,0.0003935448],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1210734,0.0001740777,0.8373395,0.0003205432,0.0002034159,0.0160026,0.0005738664,0.0140197,0.01029295],"genre_scores_gemma":[0.2918236,0.0001155029,0.6894462,0.0001944988,0.00006030891,0.008460273,0.0011607,0.001022299,0.007716704],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01629866,"threshold_uncertainty_score":0.0861966,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06364569148738479,"score_gpt":0.2915932074818623,"score_spread":0.2279475159944775,"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."}}