{"id":"W4205531478","doi":"10.5539/cis.v13n4p48","title":"Reviewer Acknowledgements for Computer and Information Science, Vol. 13, No. 4","year":2020,"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","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":[0.0008617796,0.0001587785,0.0001816548,0.0003568043,0.0005350214,0.002955685,0.001161321,0.00003421343,0.000008335161],"category_scores_gemma":[0.0009834752,0.0001365887,0.00003079081,0.001224923,0.0007118969,0.08818919,0.001299817,0.00007604097,0.0005501674],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003502871,"about_ca_system_score_gemma":0.0002446331,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001466323,"about_ca_topic_score_gemma":1.668302e-7,"domain_scores_codex":[0.998404,0.000008269855,0.0004880239,0.0003201547,0.0004253594,0.0003542412],"domain_scores_gemma":[0.9932395,0.00004210227,0.0001921609,0.00032101,0.005842524,0.0003627224],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000006591571,0.00001383357,0.0003114675,0.0002163107,0.000004435356,9.333361e-8,0.002003822,0.00008003126,0.000006702952,0.0315307,0.1005869,0.8652391],"study_design_scores_gemma":[0.0003502755,0.0001300656,0.002599153,0.00002517612,0.000001652397,0.000001604141,0.000009877107,0.5148333,0.00006437409,0.00009794669,0.4817398,0.0001468559],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001579105,0.00005076309,0.9871213,0.0005121312,0.00435588,0.0005011068,0.00001969428,0.0001064535,0.005753575],"genre_scores_gemma":[0.1478039,0.0009630219,0.7411736,0.1057167,0.003896599,0.0001570398,0.0001874544,0.00001757297,0.00008413604],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8650923,"threshold_uncertainty_score":0.9980794,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02703539167009935,"score_gpt":0.2522423689790613,"score_spread":0.225206977308962,"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."}}