{"id":"W4214763587","doi":"10.5539/ibr.v15n3p101","title":"Reviewer Acknowledgements for Computer and Information Science, Vol. 15, No. 3","year":2022,"lang":"en","type":"article","venue":"International Business Research","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Library science; Information retrieval","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03066912,0.002489615,0.005423966,0.009293258,0.005212396,0.0104703,0.005115086,0.01577641,0.1515584],"category_scores_gemma":[0.3288151,0.001471034,0.003872456,0.004173418,0.002402897,0.005563909,0.003230607,0.009031881,0.099139],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005024729,"about_ca_system_score_gemma":0.01013649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003767171,"about_ca_topic_score_gemma":0.006081582,"domain_scores_codex":[0.9634879,0.005727223,0.006794413,0.002675713,0.01970507,0.001609712],"domain_scores_gemma":[0.2864091,0.02318932,0.01015847,0.00617635,0.6636973,0.01036948],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002056213,0.000003333703,0.0000589688,0.0002203506,0.00000538223,0.00004446095,0.00001607165,0.000007314285,0.0000270388,0.00009074064,0.9956137,0.003892195],"study_design_scores_gemma":[0.0001423468,0.00003663164,0.000710604,0.001676371,0.00005928638,0.0007104524,0.0001825733,0.0002411956,0.0002240669,0.001080115,0.9948488,0.00008746872],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.0001414539,0.002875421,0.001161287,0.1207002,0.8666559,0.0006562751,0.0007911524,0.0005447385,0.006473454],"genre_scores_gemma":[0.005130731,0.00878248,0.003025756,0.1608534,0.6939016,0.00282884,0.002183,0.001442088,0.1218522],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1515584,"threshold_uncertainty_score":0.5070132,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06785576383879938,"score_gpt":0.3543088362802272,"score_spread":0.2864530724414278,"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."}}