{"id":"W4360592101","doi":"10.5267/j.dsl.2022.11.003","title":"Analytical evaluation of big data applications in E-commerce: A mixed method approach","year":2023,"lang":"en","type":"article","venue":"Decision Science Letters","topic":"Big Data and Business Intelligence","field":"Business, Management and Accounting","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Big data; Computer science; Data science; Analytics; Data collection; Process (computing); Data analysis; TOPSIS; Data mining; Operations research; Engineering","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.009148404,0.0001102116,0.0001791468,0.001329708,0.0001521264,0.0002367473,0.001998464,0.00003960171,0.00004630536],"category_scores_gemma":[0.001550723,0.00008940395,0.00003062145,0.009567038,0.0002834795,0.001619345,0.001029553,0.0001082219,0.0001915425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003596864,"about_ca_system_score_gemma":0.00006050632,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001579157,"about_ca_topic_score_gemma":0.00002142446,"domain_scores_codex":[0.9970087,0.00002557993,0.00039428,0.0006545581,0.001633836,0.0002830738],"domain_scores_gemma":[0.9980896,0.0002523753,0.0001531066,0.001199264,0.0002900213,0.00001561734],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001719359,0.0001267402,0.02379133,0.00004173125,0.000005518671,0.000001346016,0.0000456194,0.004549367,0.004207644,0.006583925,0.01764614,0.9429834],"study_design_scores_gemma":[0.0002180625,0.000001012422,0.1610385,0.00002803394,0.00003757474,8.914769e-7,0.0002702741,0.8224556,0.00009484156,0.002367965,0.01334595,0.0001412732],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4427992,0.00001634001,0.5505482,0.003021418,0.00050235,0.0005094002,0.00001847003,0.00006531268,0.002519301],"genre_scores_gemma":[0.9895321,0.000004612509,0.008625015,0.001254384,0.0002651004,0.0000469723,0.0002508724,0.00001042048,0.00001058772],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9428422,"threshold_uncertainty_score":0.4596645,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4142676290980888,"score_gpt":0.4493813758604215,"score_spread":0.03511374676233264,"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."}}