{"id":"W4376143588","doi":"10.54097/hbem.v10i.8135","title":"Research on Marketing Methods based on Machine Learning Model","year":2023,"lang":"en","type":"article","venue":"Highlights in Business Economics and Management","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Machine learning; Computer science; Artificial intelligence; Computational learning theory; Big data; Online machine learning; Instance-based learning; Plan (archaeology); Active learning (machine learning); Data science; Data mining","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003984406,0.0001409145,0.0001961324,0.001286014,0.0002570357,0.0002853886,0.0003993298,0.00004087987,0.000009858028],"category_scores_gemma":[0.00002232382,0.0001269005,0.00003771819,0.001029473,0.0000256957,0.0001463327,0.0004360503,0.0001209631,0.00004344111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007228242,"about_ca_system_score_gemma":0.00001422596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001876039,"about_ca_topic_score_gemma":0.00001107669,"domain_scores_codex":[0.9984154,0.0002382983,0.0002670304,0.0005836349,0.0001552265,0.000340468],"domain_scores_gemma":[0.9990923,0.0003604409,0.00007203136,0.0003846324,0.00003893386,0.00005163447],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001865158,0.0000311815,0.00004862988,0.00002908997,0.00001326456,0.00001013775,0.00004106704,0.5296989,0.000003650013,0.4503957,0.0002844593,0.01942531],"study_design_scores_gemma":[0.0003601089,0.00001821519,0.005013694,0.00007011813,0.000003526139,1.30998e-7,0.00002930629,0.9233956,0.00003614254,0.0007273653,0.07020755,0.0001382757],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09777467,0.0002829948,0.6517545,0.09986358,0.001928507,0.001424714,0.000005240501,0.0006783915,0.1462874],"genre_scores_gemma":[0.5051941,0.05581366,0.4206716,0.001905854,0.0002698723,0.0003130405,0.000099155,0.0001184278,0.01561425],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4496683,"threshold_uncertainty_score":0.5174853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08273429589405472,"score_gpt":0.3563704737806137,"score_spread":0.273636177886559,"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."}}