{"id":"W3135189973","doi":"10.58729/1941-6679.1460","title":"The Design, Development and Validation of a Persuasive Content Generator","year":2021,"lang":"en","type":"article","venue":"Journal of international technology and information management","topic":"Media Influence and Health","field":"Arts and Humanities","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Yale University","keywords":"Computer science; Persuasive technology; Generator (circuit theory); Social media; Domain (mathematical analysis); Content (measure theory); User-generated content; Human–computer interaction; World Wide Web; Multimedia; Internet privacy; Persuasion; Psychology; Social psychology; Power (physics)","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":[0.01016258,0.0009433545,0.0008850734,0.001418785,0.0006203055,0.002161315,0.003375291,0.00184466,0.004392551],"category_scores_gemma":[0.03116409,0.001001659,0.0005855637,0.0004490881,0.001095467,0.00294561,0.001951339,0.001579068,0.002035277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007350896,"about_ca_system_score_gemma":0.001925201,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007715733,"about_ca_topic_score_gemma":0.0003662062,"domain_scores_codex":[0.9949314,0.001936988,0.0005674316,0.000930423,0.001437938,0.0001957936],"domain_scores_gemma":[0.975122,0.01465039,0.001029356,0.003145381,0.005230728,0.0008221775],"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":[0.001660288,0.004178409,0.01524647,0.001806427,0.0002878338,0.001117084,0.006867559,0.02221682,0.2014304,0.0162926,0.008046941,0.7208492],"study_design_scores_gemma":[0.001293814,0.005304606,0.008278569,0.0003879328,0.0004112589,0.001408253,0.0008370436,0.5494912,0.3602469,0.007740347,0.06429876,0.0003013914],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07298791,0.0001017136,0.8960992,0.0002856604,0.0001514757,0.005504834,0.0002910269,0.02204496,0.002533192],"genre_scores_gemma":[0.1545088,0.00007876931,0.83648,0.0001944566,0.00003199918,0.00298994,0.0007032902,0.001448206,0.003564477],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01016258,"threshold_uncertainty_score":0.05374551,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04690145477673699,"score_gpt":0.2530420961718277,"score_spread":0.2061406413950907,"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."}}