{"id":"W4255106105","doi":"10.5539/cis.v7n2p141","title":"Reviewer Acknowledgements for Computer and Information Science, Vol. 7, No. 2","year":2014,"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":false,"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":[0.03567027,0.002235858,0.003519429,0.009656827,0.006017818,0.008869536,0.004677034,0.01650512,0.1164296],"category_scores_gemma":[0.3796024,0.001452994,0.003197203,0.004687801,0.002332309,0.006674224,0.003575025,0.01201354,0.06256602],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005732073,"about_ca_system_score_gemma":0.01156276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006133605,"about_ca_topic_score_gemma":0.01008156,"domain_scores_codex":[0.9647499,0.006624812,0.005373724,0.002727642,0.01874461,0.001779277],"domain_scores_gemma":[0.318571,0.03953999,0.007659579,0.009069734,0.615521,0.009638716],"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":[0.00001505296,0.000003467722,0.00005558916,0.0001675431,0.000004208692,0.00003710644,0.00002573997,0.000007671395,0.00003117401,0.0001747551,0.9969751,0.002502576],"study_design_scores_gemma":[0.00006327814,0.00001951286,0.00058559,0.001055746,0.0000328098,0.0003155039,0.0002034732,0.00017,0.0001607116,0.00108395,0.9962591,0.00005042967],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.00009598377,0.001667681,0.0008596068,0.1679837,0.8245222,0.0002298174,0.000482408,0.0002995504,0.003859014],"genre_scores_gemma":[0.004960078,0.00518277,0.003045242,0.2517906,0.6157805,0.00149014,0.001504019,0.001357597,0.1148892],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1164296,"threshold_uncertainty_score":0.3894959,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01675241153322003,"score_gpt":0.247088043509337,"score_spread":0.230335631976117,"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."}}