{"id":"W4290803193","doi":"10.1145/3549015.3555674","title":"ENAGRAM: An App to Evaluate Preventative Nudges for Instagram","year":2022,"lang":"en","type":"preprint","venue":"","topic":"Privacy, Security, and Data Protection","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Nudge theory; Computer science; Mobile apps; World Wide Web; Psychology; Social psychology","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002736249,0.0002336361,0.0002973359,0.0001641938,0.001053332,0.0003027072,0.001381649,0.0002352724,0.001449836],"category_scores_gemma":[0.001117029,0.0002314628,0.0001593877,0.0002616495,0.0001135138,0.0003152267,0.002108273,0.0004596617,0.00004019534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004187181,"about_ca_system_score_gemma":0.000651998,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01793173,"about_ca_topic_score_gemma":0.01358868,"domain_scores_codex":[0.9969936,0.0007952751,0.0002959899,0.00079489,0.0006832893,0.0004369672],"domain_scores_gemma":[0.9985393,0.0001356585,0.0001731544,0.0006925491,0.0001983307,0.0002609919],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0007242807,0.001548227,0.0005198801,0.000545838,0.0004280802,0.00000676856,0.2756872,0.0007769954,0.000253148,0.2130067,0.1093625,0.3971404],"study_design_scores_gemma":[0.0004897946,0.000511536,0.0005294755,0.00002584322,0.00008831538,3.525336e-7,0.02831148,0.0003760424,0.0003229846,0.3242113,0.6444778,0.0006550542],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2681462,0.001049475,0.2710326,0.04606732,0.02091862,0.05276399,0.005448852,0.004361202,0.3302117],"genre_scores_gemma":[0.8506283,0.001161378,0.07996504,0.004593272,0.004305861,0.01908758,0.00391064,0.0001834024,0.03616457],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.582482,"threshold_uncertainty_score":0.999463,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09692521396755932,"score_gpt":0.42856875749354,"score_spread":0.3316435435259807,"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."}}