{"id":"W4226187801","doi":"10.5539/cis.v15n2p89","title":"Reviewer Acknowledgements for Computer and Information Science, Vol. 15, No. 2","year":2022,"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; Data science; Library science","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":[0.03058489,0.002546896,0.005294038,0.01013231,0.005139296,0.01050742,0.004944691,0.01522392,0.1655529],"category_scores_gemma":[0.3176643,0.001529666,0.003492699,0.004378978,0.002122921,0.006008951,0.003342121,0.008382201,0.1080086],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004679357,"about_ca_system_score_gemma":0.009456685,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003306062,"about_ca_topic_score_gemma":0.0055955,"domain_scores_codex":[0.9630899,0.006013547,0.006385337,0.002753207,0.02016215,0.00159592],"domain_scores_gemma":[0.298713,0.02442954,0.009584671,0.006524237,0.650077,0.01067145],"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":[0.00001951107,0.000003330261,0.0000528965,0.0002056398,0.00000483827,0.00003970733,0.00001415385,0.00000674505,0.00002683565,0.00008588939,0.9959641,0.003576372],"study_design_scores_gemma":[0.0001291676,0.00003806269,0.0006910524,0.001505846,0.00005007428,0.0006298233,0.0001640037,0.0002088262,0.0002000449,0.0008940183,0.9954103,0.00007888141],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.0001303718,0.00294209,0.00106675,0.1125165,0.8745459,0.0005733013,0.000803553,0.0004922847,0.006929306],"genre_scores_gemma":[0.004584474,0.008634205,0.002819523,0.150407,0.6839723,0.002621045,0.002450996,0.001405046,0.1431054],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1655529,"threshold_uncertainty_score":0.5538296,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01946651010862913,"score_gpt":0.2495630443819015,"score_spread":0.2300965342732723,"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."}}