{"id":"W4288066478","doi":"10.5539/cis.v15n3p72","title":"Reviewer Acknowledgements for Computer and Information Science, Vol. 15, No. 3","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; Library science; 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":"codex-gemma-dda1882f352a","candidate_categories":["sts","scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.001722183,0.0001468061,0.0001632266,0.0006820066,0.001372012,0.002375978,0.001369616,0.00002047682,0.00002564634],"category_scores_gemma":[0.0004933893,0.0001349395,0.00003146815,0.001400211,0.000492475,0.07157446,0.00260029,0.00009957261,0.0002228443],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008839941,"about_ca_system_score_gemma":0.0003148148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001690552,"about_ca_topic_score_gemma":1.433282e-7,"domain_scores_codex":[0.9982355,0.00001464932,0.0004793379,0.0003094187,0.0005816469,0.0003794158],"domain_scores_gemma":[0.9944592,0.0000485122,0.0002172527,0.0004271492,0.004636037,0.0002118158],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000006412502,0.00002788989,0.0002818325,0.0001143116,0.000004382689,1.1295e-7,0.001518474,0.0002443262,0.000004930119,0.04406565,0.1166438,0.8370878],"study_design_scores_gemma":[0.000331429,0.0001386242,0.002616921,0.0000118994,0.000001444843,0.000004859598,0.00001588465,0.3923721,0.00002496051,0.0002086329,0.6041296,0.0001437227],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003205303,0.00007153065,0.9770577,0.0001812015,0.01085235,0.0006813331,0.0000456413,0.0001089312,0.007795984],"genre_scores_gemma":[0.2023234,0.0007093486,0.7242138,0.06795366,0.003076898,0.0007697924,0.0004462959,0.00002542636,0.0004812987],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8369441,"threshold_uncertainty_score":0.9999281,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01981926988789403,"score_gpt":0.2497164033319204,"score_spread":0.2298971334440264,"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."}}