{"id":"W4414111398","doi":"10.1177/2694104x251378449","title":"Buy Now, Pay Later: AI, Inherent Tensions, and Implications","year":2025,"lang":"en","type":"article","venue":"Management and business review.","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Key (lock); Government (linguistics); Payment; Work (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":[0.01814396,0.0002840461,0.0007281423,0.002789048,0.001977515,0.008757197,0.001517557,0.004699066,0.002774128],"category_scores_gemma":[0.0218798,0.0002809777,0.0004084494,0.004108458,0.01178881,0.009916858,0.001744132,0.008467922,0.0006269248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005546045,"about_ca_system_score_gemma":0.004212541,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007564687,"about_ca_topic_score_gemma":0.01271221,"domain_scores_codex":[0.9919878,0.00411092,0.0003903125,0.0006468017,0.002443949,0.0004201215],"domain_scores_gemma":[0.9565123,0.03712178,0.001635003,0.0005973758,0.003349307,0.0007843334],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00007681872,0.00008776262,0.001718377,0.001205672,0.00006688105,0.0003771077,0.002116487,0.001043533,0.0002689975,0.6977037,0.04992909,0.2454056],"study_design_scores_gemma":[0.00002552793,0.00005678752,0.002039403,0.002030133,0.0000288987,0.0004120672,0.005936506,0.001716728,0.000210004,0.7706013,0.2168902,0.00005237442],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.007235053,0.3662435,0.00619923,0.5476018,0.002697078,0.00002504283,0.00004520716,0.00002848484,0.06992473],"genre_scores_gemma":[0.3631517,0.4995011,0.007197865,0.115421,0.006588476,0.0001155872,0.0000625579,0.00005225029,0.007909452],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01814396,"threshold_uncertainty_score":0.09595561,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01280793959250394,"score_gpt":0.2638706537626395,"score_spread":0.2510627141701355,"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."}}