{"id":"W4206974787","doi":"10.5267/j.ijdns.2021.11.006","title":"Systematic literature review on adjustable robust counterpart for internet shopping optimization problem","year":2022,"lang":"en","type":"article","venue":"International Journal of Data and Network Science","topic":"Technology Adoption and User Behaviour","field":"Decision Sciences","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Universitas Padjadjaran; Lembaga Pengelola Dana Pendidikan; Kementerian Riset, Teknologi dan Pendidikan Tinggi","keywords":"Computer science; The Internet; Purchasing; Scopus; Systematic review; Thematic map; Thematic analysis; Peer review; Data science; Operations research; World Wide Web; Sociology; Mathematics; Engineering; Qualitative research; Social science; Operations management; Geography; MEDLINE","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":[0.009561775,0.0001014513,0.0002974528,0.0004087668,0.0002693853,0.0004982064,0.00387189,0.00002831034,0.0001291764],"category_scores_gemma":[0.001361066,0.0000713706,0.00005846626,0.0009434948,0.0001293171,0.001486707,0.0009096992,0.000276171,0.000002570652],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009486864,"about_ca_system_score_gemma":0.000146345,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":5.053884e-7,"about_ca_topic_score_gemma":0.000001634348,"domain_scores_codex":[0.9966131,0.0001320874,0.0008957245,0.0003685743,0.001809527,0.0001809637],"domain_scores_gemma":[0.9970339,0.0004170748,0.0009485798,0.0004241033,0.001098624,0.00007772515],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005784791,0.0004798782,0.007791787,0.002081188,0.0002256084,0.0001882152,0.000868529,0.3898333,0.0000899111,0.02576785,0.5523859,0.01970937],"study_design_scores_gemma":[0.001918367,0.001064924,0.0007743982,0.06028176,0.0002169272,0.003776773,0.001225415,0.8398252,0.00002115858,0.003513103,0.08680663,0.0005753794],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01103566,0.0759377,0.8791063,0.02110199,0.009038251,0.002080501,0.0008331691,0.00007999401,0.0007864236],"genre_scores_gemma":[0.8051093,0.02961066,0.1454753,0.01523563,0.001227012,0.0001472173,0.0002994963,0.00004621246,0.002849167],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7940736,"threshold_uncertainty_score":0.7195,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1136490944436591,"score_gpt":0.3951206503851932,"score_spread":0.2814715559415341,"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."}}