{"id":"W4234354495","doi":"10.5539/cis.v12n4p123","title":"Reviewer Acknowledgements for Computer and Information Science, Vol. 12, No. 4","year":2019,"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; Library science; Data 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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.03431056,0.002714403,0.005950598,0.01115619,0.005167734,0.009199138,0.005481915,0.0150745,0.1440409],"category_scores_gemma":[0.3708347,0.00167535,0.004031409,0.004655364,0.002566047,0.006147719,0.003633065,0.008722205,0.08024862],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005419251,"about_ca_system_score_gemma":0.009837684,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003627368,"about_ca_topic_score_gemma":0.005571943,"domain_scores_codex":[0.9604873,0.006901448,0.007814758,0.002719818,0.02038415,0.001692516],"domain_scores_gemma":[0.2431328,0.02535587,0.01117203,0.006684564,0.7045433,0.009111472],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002776722,0.000004117632,0.00008785024,0.0003559676,0.000007982193,0.00006517893,0.00002598156,0.000009645798,0.00003972342,0.0001274765,0.9943779,0.004870435],"study_design_scores_gemma":[0.0001638276,0.00004133329,0.0008392176,0.002068145,0.0000830707,0.0008862336,0.0002584541,0.0002718336,0.0002831485,0.001350881,0.9936472,0.000106647],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.0001685389,0.003321997,0.001260311,0.1199012,0.8683074,0.0006433537,0.0007225981,0.0004478008,0.005226796],"genre_scores_gemma":[0.006080807,0.00933437,0.003750951,0.1437269,0.7116419,0.003073473,0.002000354,0.00133717,0.119054],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9656894,"threshold_uncertainty_score":0.4818649,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01740724556296689,"score_gpt":0.2458715093260979,"score_spread":0.228464263763131,"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."}}