{"id":"W4234230271","doi":"10.5539/cis.v14n2p109","title":"Reviewer Acknowledgements for Computer and Information Science, Vol. 14, No. 2","year":2021,"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","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":["scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.001127367,0.000153024,0.000179829,0.0004403242,0.0006306062,0.00359535,0.0008887242,0.00003870105,0.00001230652],"category_scores_gemma":[0.001336403,0.0001358675,0.00003360089,0.001327616,0.0005299545,0.08482472,0.001403712,0.00007433439,0.0003814427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005093244,"about_ca_system_score_gemma":0.0004457572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":8.119085e-7,"about_ca_topic_score_gemma":3.000051e-7,"domain_scores_codex":[0.9983445,0.000010976,0.0004892703,0.0003302921,0.0004492036,0.0003758038],"domain_scores_gemma":[0.9852544,0.00005270672,0.0001753371,0.0004663101,0.01380472,0.0002465071],"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":[0.000002847118,0.00002186694,0.0002305672,0.0001650442,0.000004699078,2.23289e-7,0.0008438136,0.00004314225,0.000009791464,0.04178825,0.07148369,0.8854061],"study_design_scores_gemma":[0.0004179482,0.00007332739,0.004597052,0.00004987549,0.000002267456,0.000007769424,0.00001018789,0.3233551,0.0002399053,0.0002827532,0.670781,0.0001827904],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001853318,0.00009594952,0.977684,0.0001730113,0.009445085,0.0003536664,0.00001992043,0.00007987273,0.01029517],"genre_scores_gemma":[0.0422511,0.001296986,0.9174037,0.03594708,0.002247789,0.0001351738,0.000255146,0.00001349331,0.0004495162],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8852233,"threshold_uncertainty_score":0.997439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02069090286130638,"score_gpt":0.2559217234238629,"score_spread":0.2352308205625565,"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."}}