{"id":"W4246529221","doi":"10.5539/cis.v11n1p108","title":"Reviewer Acknowledgements for Computer and Information Science, Vol. 11, No. 1","year":2018,"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; Human–computer interaction","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":[0.04367598,0.002680256,0.006429004,0.01196393,0.005685893,0.0101649,0.005547804,0.01490965,0.1243447],"category_scores_gemma":[0.4638543,0.001729673,0.003979077,0.005096638,0.002753632,0.006981324,0.00392661,0.01008638,0.07229072],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00606333,"about_ca_system_score_gemma":0.01085164,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003573559,"about_ca_topic_score_gemma":0.005714481,"domain_scores_codex":[0.9484135,0.009331928,0.01057644,0.004074578,0.02555675,0.002046832],"domain_scores_gemma":[0.1869876,0.03237507,0.01256824,0.007156504,0.7521219,0.008790608],"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":[0.0000259241,0.000004009002,0.00008800297,0.0004229869,0.00000784344,0.00005334887,0.00003484426,0.000009927526,0.00003385848,0.0001350666,0.9943963,0.00478798],"study_design_scores_gemma":[0.0001428013,0.0000398993,0.0009069865,0.002847168,0.00008009599,0.0008341722,0.0003020302,0.0002462453,0.0002468413,0.001444522,0.992796,0.0001132018],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.0001418528,0.003742243,0.001133922,0.1318107,0.8573129,0.0005867255,0.0007758279,0.0004054203,0.004090481],"genre_scores_gemma":[0.005609819,0.01027294,0.00338312,0.1569559,0.7342063,0.003114831,0.0021267,0.001319475,0.08301096],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1243447,"threshold_uncertainty_score":0.4159744,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02203078185172409,"score_gpt":0.2627610459177459,"score_spread":0.2407302640660218,"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."}}