{"id":"W4367852911","doi":"10.5539/cis.v16n2p63","title":"Reviewer Acknowledgements for Computer and Information Science, Vol. 16, No. 2","year":2023,"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; World Wide Web; 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":[0.02848717,0.002378993,0.004933723,0.009351732,0.004882356,0.00992504,0.004662792,0.01449478,0.1632113],"category_scores_gemma":[0.3011371,0.001434532,0.003365951,0.004136126,0.00204539,0.005637405,0.003117215,0.008398256,0.1056309],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004696484,"about_ca_system_score_gemma":0.009476994,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003411333,"about_ca_topic_score_gemma":0.005780608,"domain_scores_codex":[0.9665849,0.005392135,0.005781426,0.002443148,0.0182733,0.001525055],"domain_scores_gemma":[0.3155132,0.02295006,0.009346161,0.006154807,0.6353414,0.01069438],"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":[0.00001885935,0.000003063347,0.000052206,0.0001889937,0.000004345096,0.00003941133,0.00001368829,0.000006545824,0.00002647812,0.00008784892,0.996022,0.003536566],"study_design_scores_gemma":[0.0001238824,0.00003482872,0.0006746887,0.001445126,0.00004691891,0.0006550702,0.0001598446,0.000205291,0.0001994116,0.0009307349,0.995449,0.00007509929],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.0001324359,0.002894175,0.00105783,0.1150876,0.8721857,0.0005413138,0.0007525223,0.0004668987,0.00688153],"genre_scores_gemma":[0.004776313,0.008749724,0.002819317,0.15026,0.6808187,0.002487486,0.002319419,0.0014105,0.1463584],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1632113,"threshold_uncertainty_score":0.5459963,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02545232626805092,"score_gpt":0.2659466571246082,"score_spread":0.2404943308565573,"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."}}