{"id":"W4415051922","doi":"10.34925/eip.2025.181.8.164","title":"ВЛИЯНИЕ МОБИЛЬНОЙ ОПТИМИЗАЦИИ НА КОНВЕРСИЮ ИНТЕРНЕТ-МАГАЗИНОВ","year":2025,"lang":"ru","type":"article","venue":"Экономика и предпринимательство","topic":"Consumer Retail Behavior Studies","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Process (computing); Payment; Key (lock); Download; Mobile device; Volume (thermodynamics); E-commerce","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006415908,0.0008994511,0.0005609981,0.003487167,0.003896917,0.01653398,0.001576427,0.00289996,0.03829527],"category_scores_gemma":[0.01287158,0.000791728,0.00110775,0.004131862,0.004379803,0.007538741,0.004523364,0.003842157,0.01471688],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006974432,"about_ca_system_score_gemma":0.01701187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01712162,"about_ca_topic_score_gemma":0.01937517,"domain_scores_codex":[0.9900849,0.002496591,0.0004624814,0.001326619,0.004626726,0.001002785],"domain_scores_gemma":[0.9918231,0.002001101,0.0007688782,0.001122613,0.003342605,0.0009416272],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.00014279,0.0001471367,0.008948335,0.00105438,0.0001039552,0.0005050675,0.005934721,0.002498064,0.004316593,0.7286243,0.05220446,0.1955202],"study_design_scores_gemma":[0.00002699918,0.00006004329,0.007764905,0.0007530936,0.00007547149,0.0003659654,0.00510862,0.001272261,0.003034454,0.1200077,0.8614153,0.0001150956],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.03187995,0.0158976,0.06890213,0.03161388,0.001793927,0.000371638,0.002225843,0.0007994912,0.8465155],"genre_scores_gemma":[0.6528224,0.02851938,0.08376571,0.004975731,0.001151897,0.001084716,0.002894405,0.001019949,0.2237658],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03829527,"threshold_uncertainty_score":0.1281104,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0178896072499671,"score_gpt":0.2598412672892844,"score_spread":0.2419516600393173,"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."}}