{"id":"W4235931669","doi":"10.5539/cis.v13n3p103","title":"Reviewer Acknowledgements for Computer and Information Science, Vol. 13, No. 3","year":2020,"lang":"en","type":"article","venue":"Computer and Information Science","topic":"Big Data and Digital Economy","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer 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":["scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.0008612192,0.0001587695,0.00018162,0.0003566697,0.0005348056,0.002954413,0.00116063,0.00003421108,0.000008450042],"category_scores_gemma":[0.0009947573,0.0001365677,0.00003078888,0.00122505,0.0007117933,0.08817966,0.001299416,0.00007604289,0.0005594427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000351384,"about_ca_system_score_gemma":0.000245379,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001476966,"about_ca_topic_score_gemma":1.662772e-7,"domain_scores_codex":[0.9984041,0.000008270735,0.0004878825,0.0003201288,0.0004253811,0.0003542086],"domain_scores_gemma":[0.993151,0.00004203484,0.0001921265,0.0003208591,0.005931254,0.0003626919],"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":[0.000006533371,0.00001382132,0.000310756,0.0002175912,0.000004433176,9.30268e-8,0.00200123,0.00008090941,0.000006784187,0.03062461,0.1013544,0.8653789],"study_design_scores_gemma":[0.0003493977,0.0001275627,0.002574362,0.00002498401,0.000001633003,0.000001581678,0.00000979657,0.51136,0.00006509349,0.00009659302,0.485243,0.0001459917],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001586083,0.0000506454,0.987063,0.0005132185,0.004390378,0.0005010787,0.00001985577,0.0001064053,0.005769365],"genre_scores_gemma":[0.1453935,0.0009664784,0.7432434,0.1060038,0.003942634,0.0001575937,0.0001880388,0.00001763958,0.0000868817],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8652329,"threshold_uncertainty_score":0.9980806,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02681177213026827,"score_gpt":0.2518220705176151,"score_spread":0.2250102983873468,"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."}}