{"id":"W4255489682","doi":"10.5539/cis.v12n3p117","title":"Reviewer Acknowledgements for Computer and Information Science, Vol. 12, No. 3","year":2019,"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; 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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.03485449,0.002673323,0.005951696,0.01059229,0.005163166,0.009858175,0.005169119,0.01524411,0.1410306],"category_scores_gemma":[0.3618498,0.001608579,0.00422783,0.004873459,0.002591165,0.005703695,0.00343847,0.00895859,0.08450703],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005382921,"about_ca_system_score_gemma":0.01004306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003681887,"about_ca_topic_score_gemma":0.005702341,"domain_scores_codex":[0.9581131,0.00692327,0.008088035,0.002909011,0.02222849,0.001738039],"domain_scores_gemma":[0.2419113,0.02464385,0.01126655,0.006642872,0.7063189,0.009216546],"domain_codex":null,"domain_gemma":"evaluation","domain_candidate":"evaluation","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002561801,0.000003917421,0.0000816958,0.0003181832,0.000007179696,0.0000619949,0.00002628216,0.000009176099,0.0000385295,0.0001245123,0.99454,0.004762834],"study_design_scores_gemma":[0.0001563174,0.00003804291,0.0008282306,0.002171819,0.00007678425,0.0009698473,0.0002475813,0.0002903955,0.0002895857,0.001403688,0.9934207,0.000106908],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.0001751896,0.003601056,0.00152645,0.1223086,0.8638885,0.0007717786,0.000807523,0.0005739093,0.00634698],"genre_scores_gemma":[0.006520306,0.009907505,0.00396845,0.1612196,0.6995128,0.003225139,0.002101101,0.001651712,0.1118934],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.9651455,"threshold_uncertainty_score":0.4717942,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01726281663400575,"score_gpt":0.2454613494963215,"score_spread":0.2281985328623157,"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."}}