{"id":"W4396514371","doi":"10.5539/cis.v17n1p57","title":"Reviewer Acknowledgements for Computer and Information Science, Vol. 17, No. 1","year":2024,"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; Data 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.03371361,0.002355437,0.005416646,0.01087998,0.005517667,0.01001402,0.005110465,0.01459532,0.1618345],"category_scores_gemma":[0.3675151,0.001523598,0.003473469,0.004699902,0.002260986,0.00613278,0.003454052,0.009095754,0.1035484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00540521,"about_ca_system_score_gemma":0.01101697,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003695884,"about_ca_topic_score_gemma":0.006419904,"domain_scores_codex":[0.9608164,0.006718366,0.00705824,0.00296262,0.020721,0.001723388],"domain_scores_gemma":[0.260359,0.02764704,0.01043858,0.006392653,0.6849669,0.01019584],"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":[0.00001810014,0.000003095768,0.00005344446,0.0002177885,0.000004434867,0.00003427926,0.00001650942,0.000006575,0.00002320916,0.00009217525,0.9959359,0.003594527],"study_design_scores_gemma":[0.0001177329,0.00003566424,0.0006843758,0.001708783,0.00005050116,0.0005618295,0.0001872833,0.0001834019,0.0001848632,0.001027501,0.9951762,0.00008183534],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.0001263453,0.003010438,0.001031758,0.1286923,0.859319,0.0005608932,0.0008546171,0.0004674043,0.005937262],"genre_scores_gemma":[0.004644281,0.009480145,0.003091909,0.1585928,0.687574,0.002843251,0.002724627,0.001509151,0.1295398],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1618345,"threshold_uncertainty_score":0.5413904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02056657501348732,"score_gpt":0.2637836315254728,"score_spread":0.2432170565119855,"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."}}