{"id":"W4231255418","doi":"10.5539/cis.v8n4p105","title":"Reviewer Acknowledgements for Computer and Information Science, Vol. 8, No. 4","year":2015,"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","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":[0.001762336,0.0001516014,0.0001681346,0.000571127,0.0004373271,0.003025376,0.001082054,0.00003584692,0.00000374216],"category_scores_gemma":[0.001477571,0.000127545,0.00002442307,0.001077834,0.000613595,0.1026182,0.001226073,0.00006437134,0.0005066902],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006807515,"about_ca_system_score_gemma":0.0004117322,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001847021,"about_ca_topic_score_gemma":2.095563e-7,"domain_scores_codex":[0.9983857,0.000009312952,0.0004634254,0.0002782032,0.0004969668,0.0003664072],"domain_scores_gemma":[0.9861867,0.00003756647,0.0001884289,0.0004122965,0.01279221,0.0003827361],"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":[0.000005643986,0.00001852738,0.0003853648,0.00009917984,0.000003491681,6.811037e-8,0.001513805,0.00006821804,0.00000185056,0.03391829,0.1588439,0.8051417],"study_design_scores_gemma":[0.0004725232,0.0001332273,0.002878544,0.00002971913,0.000001588608,0.000002930415,0.00001271686,0.410253,0.00004394196,0.0003505119,0.5856651,0.0001561753],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002150648,0.00005492488,0.9764413,0.0001094685,0.0103513,0.0004805943,0.00001413131,0.00009356377,0.01030407],"genre_scores_gemma":[0.07203779,0.0004524303,0.8961183,0.02742411,0.003419807,0.0001620073,0.0001565365,0.00001386217,0.0002151107],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8049855,"threshold_uncertainty_score":0.9980096,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03438602655899332,"score_gpt":0.2682675730258988,"score_spread":0.2338815464669055,"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."}}