{"id":"W4414441846","doi":"10.2139/ssrn.5520195","title":"Credit, Privacy, and Data Monetization by Digital Platforms","year":2025,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Blockchain Technology Applications and Security","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Wilfrid Laurier University","funders":"","keywords":"Monetization; Monopolistic competition; Subsidy; Incentive; Financial services; Competition (biology); Big data","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":[0.007097316,0.0004636313,0.001225245,0.001375145,0.003417627,0.009599704,0.001667286,0.003829568,0.01090757],"category_scores_gemma":[0.03800064,0.0007344759,0.0008549083,0.002997761,0.008000962,0.0193283,0.006142695,0.004849909,0.0008988677],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003384047,"about_ca_system_score_gemma":0.004646781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002736606,"about_ca_topic_score_gemma":0.002139122,"domain_scores_codex":[0.9944028,0.002156755,0.0003835711,0.0009756869,0.001089187,0.0009919319],"domain_scores_gemma":[0.962503,0.02195721,0.003525993,0.008946748,0.001510478,0.001556721],"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":[0.0004056497,0.00006314674,0.001437034,0.00004276538,0.00001797497,0.0001078127,0.000356783,0.007554332,0.000742966,0.9773237,0.0008662886,0.01108166],"study_design_scores_gemma":[0.00005141016,0.00003221808,0.0002209594,0.00001859802,0.00001270328,0.00006976083,0.0001012968,0.02438953,0.000929154,0.9721665,0.00199034,0.00001751673],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5353183,0.001950013,0.3371809,0.01753252,0.0003753593,0.0002209343,0.0007568137,0.0004994382,0.1061657],"genre_scores_gemma":[0.9839149,0.0003480677,0.0043318,0.0001573442,0.00008443104,0.00004894506,0.00006257244,0.00003356667,0.01101857],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01090757,"threshold_uncertainty_score":0.03753465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01092426255838547,"score_gpt":0.2544747167356303,"score_spread":0.2435504541772449,"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."}}