{"id":"W4231970171","doi":"10.5539/cis.v9n1p147","title":"Reviewer Acknowledgements for Computer and Information Science, Vol. 9, No. 1","year":2016,"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; 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":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.001267024,0.0001513746,0.0001593515,0.0005592611,0.000525362,0.002085763,0.001074462,0.00003492011,0.00001124795],"category_scores_gemma":[0.001211739,0.0001028941,0.00002829503,0.0008430714,0.0007377359,0.1063436,0.001126088,0.00004238651,0.0006185091],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005891583,"about_ca_system_score_gemma":0.000238901,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":8.699149e-7,"about_ca_topic_score_gemma":1.615592e-7,"domain_scores_codex":[0.9984384,0.00000829258,0.0004646888,0.0002983166,0.0004048676,0.0003854743],"domain_scores_gemma":[0.9905353,0.00007125123,0.0001925508,0.0004336899,0.008518465,0.0002488067],"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":[0.00000276345,0.000008620477,0.00026519,0.00005588372,0.000002158878,2.903194e-8,0.0003066191,0.000003697553,0.00001007473,0.02664127,0.04391905,0.9287847],"study_design_scores_gemma":[0.0006793688,0.0001533682,0.01028494,0.00009297486,0.0000020829,0.000003381909,0.000004802962,0.1560642,0.0002075888,0.0004929118,0.8317813,0.0002331025],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002078021,0.0000298248,0.9849023,0.0001913957,0.007319502,0.0004149963,0.0000207388,0.00008412194,0.004959148],"genre_scores_gemma":[0.148433,0.001564601,0.8127914,0.03218872,0.004199686,0.0002526172,0.00008403099,0.00001951738,0.0004663655],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9285516,"threshold_uncertainty_score":0.9989502,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02005128127764308,"score_gpt":0.2513886848851868,"score_spread":0.2313374036075437,"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."}}