{"id":"W4251259613","doi":"10.5539/cis.v13n2p87","title":"Reviewer Acknowledgements for Computer and Information Science, Vol. 13, No. 2","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; 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":[0.02834157,0.002304069,0.00440314,0.009221578,0.00467624,0.0104326,0.004729475,0.01463762,0.1814285],"category_scores_gemma":[0.2942847,0.001458344,0.00334221,0.004161416,0.001991536,0.006248254,0.003173849,0.008327261,0.1169306],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004592584,"about_ca_system_score_gemma":0.01006459,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003310024,"about_ca_topic_score_gemma":0.006062534,"domain_scores_codex":[0.9671916,0.005299623,0.005314898,0.00236846,0.01823112,0.001594289],"domain_scores_gemma":[0.3182741,0.02172174,0.008990711,0.005918739,0.6334416,0.01165319],"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":[0.00001672,0.000003032906,0.00004656851,0.0001786112,0.000003751573,0.00002917662,0.00001032385,0.000006374464,0.00002172113,0.00008832095,0.9961817,0.003413735],"study_design_scores_gemma":[0.0001054293,0.00003271788,0.0006095681,0.001346645,0.0000407193,0.0005089727,0.0001294633,0.0001777163,0.0001761059,0.0009280482,0.9958766,0.00006803746],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.0001212152,0.003001714,0.001079708,0.1206779,0.8647935,0.0004998834,0.0008925684,0.0005033307,0.008430181],"genre_scores_gemma":[0.00407046,0.009012622,0.002809067,0.150282,0.6702098,0.002152801,0.002673647,0.00139347,0.1573962],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1814285,"threshold_uncertainty_score":0.6069388,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02633485371931979,"score_gpt":0.2516663285142493,"score_spread":0.2253314747949295,"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."}}