{"id":"W4205531478","doi":"10.5539/cis.v13n4p48","title":"Reviewer Acknowledgements for Computer and Information Science, Vol. 13, No. 4","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02808968,0.002170745,0.00422981,0.008916809,0.004705087,0.009908396,0.004929822,0.01464725,0.186846],"category_scores_gemma":[0.2921943,0.001422685,0.003456899,0.004045008,0.002051565,0.006035865,0.003169612,0.008219172,0.1173141],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004917559,"about_ca_system_score_gemma":0.01079781,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003646194,"about_ca_topic_score_gemma":0.006610444,"domain_scores_codex":[0.969156,0.004965903,0.005030811,0.002080364,0.01719346,0.001573473],"domain_scores_gemma":[0.31588,0.02059906,0.008725632,0.005733802,0.6374298,0.01163165],"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":[0.00001717557,0.000003040757,0.00005183764,0.0001764418,0.000003876749,0.0000297382,0.000009923228,0.000006877206,0.00002148681,0.00009603905,0.9959709,0.003612556],"study_design_scores_gemma":[0.0001077337,0.00003248669,0.0006069547,0.001266045,0.00004399354,0.0004775353,0.0001300149,0.000177785,0.0001785797,0.001034695,0.9958759,0.00006836868],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.0001324999,0.002878143,0.001130819,0.1301867,0.855119,0.0005148991,0.000893591,0.0004999602,0.008644329],"genre_scores_gemma":[0.00439108,0.00922841,0.003134665,0.1504817,0.65144,0.002206894,0.002723339,0.001376861,0.175017],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.186846,"threshold_uncertainty_score":0.6250622,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02703539167009935,"score_gpt":0.2522423689790613,"score_spread":0.225206977308962,"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."}}