{"id":"W2113024478","doi":"10.1111/j.1360-0443.2010.03050.x","title":"Losses disguised as wins in modern multi‐line video slot machines","year":2010,"lang":"en","type":"article","venue":"Addiction","topic":"Gambling Behavior and Treatments","field":"Psychology","cited_by":181,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Line (geometry); Computer science; Psychology; Internet privacy; Mathematics","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":[0.0004108539,0.0002959653,0.0001284531,0.0002225379,0.0002173792,0.0005664623,0.0002948933,0.0003707491,0.003511922],"category_scores_gemma":[0.001837827,0.0001521765,0.0001214984,0.00007262523,0.0005378021,0.0004606878,0.0005904448,0.0004077734,0.0002970423],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002268114,"about_ca_system_score_gemma":0.000101803,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004491714,"about_ca_topic_score_gemma":0.00129252,"domain_scores_codex":[0.999763,0.00005771171,0.00001540308,0.00004028227,0.00008461233,0.00003908755],"domain_scores_gemma":[0.999406,0.0001960692,0.0002184513,0.00003151285,0.0000386116,0.0001093545],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.009725394,0.006271218,0.3223247,0.0009402059,0.000210373,0.003015343,0.006996012,0.002937665,0.3477247,0.002265093,0.002540156,0.2950493],"study_design_scores_gemma":[0.0001571258,0.009205432,0.9396622,0.0001221164,0.00004970833,0.0036177,0.003130288,0.005898582,0.03159435,0.001200345,0.005309898,0.00005226237],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9979516,0.00003548989,0.0007197388,0.0000249973,0.00000769652,0.00001875249,0.00001315467,0.00001597742,0.001212663],"genre_scores_gemma":[0.997352,0.00004232314,0.0009428344,0.00002918374,0.000006847776,0.00002281143,0.00003032965,0.000005305421,0.001568365],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003511922,"threshold_uncertainty_score":0.01174861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05572237453826141,"score_gpt":0.3875339485839059,"score_spread":0.3318115740456445,"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."}}