{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00144914,0.00006179986,0.0000738937,0.0005892109,0.0004594049,0.0008640349,0.00150166,0.00001278428,0.0002367597],"category_scores_gemma":[0.003746814,0.00005944421,0.00001851343,0.0009514336,0.0001548299,0.006370012,0.002569136,0.0001153163,0.0004870125],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001460278,"about_ca_system_score_gemma":0.000252829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008553026,"about_ca_topic_score_gemma":9.627548e-7,"domain_scores_codex":[0.9984908,0.00002624932,0.0001912328,0.0002550945,0.0007984336,0.0002381509],"domain_scores_gemma":[0.9758785,0.0001008755,0.00004830736,0.000248264,0.02365843,0.00006558791],"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":[0.0000264368,0.0001173698,0.001313764,0.00008288831,0.00001869763,0.000001367893,0.0001328528,0.0001167316,0.00002384448,0.02900661,0.7246853,0.2444742],"study_design_scores_gemma":[0.0002922105,0.00003797891,0.008697968,0.00001343247,4.317098e-7,0.00000176555,0.00000632056,0.0344279,0.00002096982,0.001237715,0.9551923,0.00007095758],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01066486,0.0004824791,0.7934071,0.00696378,0.07669723,0.002660234,0.0004671043,0.0002139233,0.1084433],"genre_scores_gemma":[0.6179339,0.001736844,0.284001,0.02006843,0.02400492,0.007384475,0.003279445,0.0001204776,0.04147046],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.607269,"threshold_uncertainty_score":0.8331908,"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."}}