{"id":"W4307866166","doi":"10.5539/cis.v15n4p80","title":"Reviewer Acknowledgements for Computer and Information Science, Vol. 15, No. 4","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","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":[0.02969822,0.002381913,0.005093134,0.009664702,0.005154999,0.009913515,0.005115845,0.01507949,0.1705014],"category_scores_gemma":[0.312871,0.001473798,0.003602362,0.004190163,0.002179164,0.005737279,0.003301073,0.008260661,0.1077686],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005002256,"about_ca_system_score_gemma":0.01004435,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003670845,"about_ca_topic_score_gemma":0.006161296,"domain_scores_codex":[0.9659212,0.005487452,0.005946243,0.002376262,0.01872932,0.001539564],"domain_scores_gemma":[0.2980601,0.02269528,0.009270411,0.006202715,0.6532457,0.01052592],"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":[0.00001982672,0.000003277179,0.00005893661,0.000200929,0.000004975122,0.00004008104,0.00001341041,0.000007182736,0.00002622049,0.0000922406,0.9957813,0.003751611],"study_design_scores_gemma":[0.0001313844,0.00003736914,0.0006882929,0.001409018,0.0000541134,0.0005881389,0.0001638669,0.000208836,0.000200632,0.0009933879,0.995446,0.00007904555],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.0001415171,0.002825904,0.001111867,0.1208214,0.866107,0.0005932366,0.0007945718,0.0004877176,0.007116609],"genre_scores_gemma":[0.004992647,0.008866489,0.003130367,0.1504933,0.6654429,0.002678352,0.002465089,0.001378078,0.1605529],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1705014,"threshold_uncertainty_score":0.5703841,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01998456725953239,"score_gpt":0.2501311193730197,"score_spread":0.2301465521134873,"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."}}