{"id":"W4252653364","doi":"10.5539/cis.v10n4p81","title":"Reviewer Acknowledgements for Computer and Information Science, Vol. 10, No. 4","year":2017,"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0388476,0.002844262,0.0064667,0.01050663,0.005332774,0.009908055,0.005917994,0.01652557,0.1230807],"category_scores_gemma":[0.4167588,0.001768144,0.004403473,0.004515043,0.002911479,0.006663939,0.003879024,0.009731444,0.06825237],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005978351,"about_ca_system_score_gemma":0.01063155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003785882,"about_ca_topic_score_gemma":0.005716855,"domain_scores_codex":[0.9547825,0.007947514,0.009450426,0.003177423,0.02268115,0.001961083],"domain_scores_gemma":[0.2173274,0.02705394,0.0120795,0.006756017,0.7274998,0.009283386],"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":[0.00003192352,0.000004461089,0.0001019321,0.0004264227,0.000009914505,0.00007210498,0.00002944463,0.00001115802,0.00003986544,0.0001344067,0.9943081,0.004830417],"study_design_scores_gemma":[0.0002054342,0.00004388465,0.0009382617,0.002547867,0.0000996259,0.0009854387,0.0002993454,0.0003166921,0.0002979325,0.001578212,0.9925665,0.0001207585],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.0001607818,0.00316494,0.001135941,0.1204192,0.8692766,0.0006570516,0.0006791612,0.0004034156,0.004102833],"genre_scores_gemma":[0.00604433,0.008935436,0.003520072,0.1511065,0.7321791,0.00333214,0.001789194,0.001202974,0.09189014],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.1230807,"threshold_uncertainty_score":0.4117458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02843096815004034,"score_gpt":0.2761180709127785,"score_spread":0.2476871027627382,"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."}}