{"id":"W4391442460","doi":"10.1111/add.16438","title":"Beyond ‘single customer view’: Player tracking's potential role in understanding and reducing gambling‐related harm","year":2024,"lang":"en","type":"article","venue":"Addiction","topic":"Gambling Behavior and Treatments","field":"Psychology","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Alberta Gambling Research Institute, University of Calgary; New South Wales Government; Responsible Gambling Fund; Gambling Research Exchange Ontario","keywords":"Harm reduction; Harm; Computer science; Argument (complex analysis); Government (linguistics); Computer security; Tracking (education); Risk analysis (engineering); Psychology; Internet privacy; Business; Medicine; Social psychology; Public health","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001947718,0.0001559415,0.0001480531,0.000400378,0.0001129948,0.0001192432,0.00004286692,0.0001817582,0.0006786922],"category_scores_gemma":[0.00000676593,0.0001560007,0.00005822906,0.0003772161,0.00004091232,0.0002355484,0.00001809276,0.0002867019,0.0002204134],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002456555,"about_ca_system_score_gemma":0.0000149406,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002526265,"about_ca_topic_score_gemma":0.00002314334,"domain_scores_codex":[0.9988343,0.0000612143,0.0002617875,0.000421702,0.0001432933,0.0002777584],"domain_scores_gemma":[0.9997019,0.00003869272,0.00004299939,0.0001378602,0.00001545178,0.00006310825],"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":[0.0006407615,0.002934117,0.07526663,0.0001204443,0.001787529,0.002448236,0.05950957,0.0009800433,0.1464755,0.02753695,0.00832513,0.6739751],"study_design_scores_gemma":[0.0191501,0.00222538,0.8647571,0.003153799,0.003725215,0.003137922,0.02103529,0.01258439,0.01402424,0.02780706,0.02502806,0.003371482],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9811437,0.002459932,0.0003530078,0.0001298924,0.00267712,0.0001977153,0.00001552955,0.0002353756,0.01278771],"genre_scores_gemma":[0.9988886,0.00004901844,0.00003741828,0.00002045126,0.0001013533,0.00002326893,0.00005207595,0.00004035492,0.0007874321],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7894905,"threshold_uncertainty_score":0.7431204,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08521922888793128,"score_gpt":0.3551088979028684,"score_spread":0.2698896690149372,"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."}}