{"id":"W4251610925","doi":"10.5539/cis.v7n4p143","title":"Reviewer Acknowledgements for Computer and Information Science, Vol. 7, No. 4","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":true,"ca_institutions":"","funders":"","keywords":"Computer science; Library 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":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.001743344,0.0001542382,0.0001740774,0.0005605986,0.0006269663,0.00298045,0.001097659,0.00003596555,0.000006244476],"category_scores_gemma":[0.001376967,0.0001299602,0.00002810782,0.0009338935,0.0006166668,0.08468682,0.001078924,0.00006534187,0.000452266],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004080117,"about_ca_system_score_gemma":0.000171941,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001262268,"about_ca_topic_score_gemma":1.849933e-7,"domain_scores_codex":[0.9984423,0.00001125384,0.0004677385,0.0002941995,0.0004114522,0.0003730752],"domain_scores_gemma":[0.9909622,0.0000644638,0.0001979069,0.0004472545,0.008077803,0.0002503523],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000002432973,0.00001086503,0.0002342529,0.0001040479,0.000002172819,1.515912e-8,0.0005163254,0.00003642701,0.000003049434,0.05133809,0.04277263,0.9049797],"study_design_scores_gemma":[0.0003052434,0.0001027852,0.005385851,0.00003001247,0.000001345913,0.000001589092,0.000003304688,0.4737262,0.00004991947,0.0003052181,0.5199543,0.0001342416],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001770943,0.0000220644,0.9805272,0.00009330616,0.007426092,0.0003864859,0.000008918109,0.00008341198,0.009681582],"genre_scores_gemma":[0.1241073,0.0004632146,0.8374519,0.03396649,0.003551726,0.000149398,0.0001300056,0.00001363618,0.0001663969],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9048455,"threshold_uncertainty_score":0.9980546,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0172042162340428,"score_gpt":0.247658693746378,"score_spread":0.2304544775123352,"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."}}