{"id":"W4403204721","doi":"10.1093/heapro/daae037","title":"Dark patterns, dark nudges, sludge and misinformation: alcohol industry apps and digital tools","year":2024,"lang":"en","type":"article","venue":"Health Promotion International","topic":"Substance Abuse Treatment and Outcomes","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Medical Research Council","keywords":"Nudge theory; Misinformation; Alcohol industry; mHealth; Applied psychology; Social marketing; Psychology; Environmental health; Internet privacy; Medicine; Social psychology; Business; Advertising; Marketing; Psychological intervention; Computer security; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001401522,0.0001326103,0.0001608057,0.0001530912,0.00008197923,0.0002260555,0.00004267746,0.0001101094,0.0002261325],"category_scores_gemma":[0.00004434353,0.0001105211,0.00003542216,0.00008906295,0.00003847231,0.0008130265,0.00003071615,0.0002583731,0.00004782762],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001618047,"about_ca_system_score_gemma":0.0001202021,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006326861,"about_ca_topic_score_gemma":0.000005033637,"domain_scores_codex":[0.9989773,0.00001520093,0.0003207582,0.0002190115,0.0002994893,0.0001682312],"domain_scores_gemma":[0.9995547,0.00006066821,0.00006795538,0.00009869872,0.00006459292,0.0001533814],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001019251,0.0002241162,0.5808349,0.000628176,0.0002737645,0.00008856201,0.00359941,9.229308e-7,0.00003050793,0.004495931,0.02730216,0.3824196],"study_design_scores_gemma":[0.005895064,0.0008183305,0.8986099,0.002758263,0.00007946189,0.001491326,0.001714839,0.001495261,0.0001986459,0.001332544,0.0851524,0.0004540052],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9704819,0.001232273,0.0005478833,0.02133344,0.0007531786,0.000505004,0.00009240975,0.0001657341,0.004888151],"genre_scores_gemma":[0.9952641,0.0005069302,0.0001797559,0.001074671,0.0002769586,0.00003674648,0.0006690696,0.0000149977,0.001976773],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3819656,"threshold_uncertainty_score":0.4506918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06259517244245016,"score_gpt":0.3555973135554822,"score_spread":0.2930021411130321,"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."}}