{"id":"W4367852911","doi":"10.5539/cis.v16n2p63","title":"Reviewer Acknowledgements for Computer and Information Science, Vol. 16, No. 2","year":2023,"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; World Wide Web; 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","insufficient_payload"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.001631892,0.0001545542,0.0001688331,0.0008931403,0.0007000496,0.002999916,0.001110371,0.0000369887,0.000007240374],"category_scores_gemma":[0.0008722121,0.0001328582,0.00003102189,0.00215494,0.000573819,0.08419795,0.001442878,0.00006686784,0.001192865],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006047595,"about_ca_system_score_gemma":0.0002407548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001620235,"about_ca_topic_score_gemma":2.600223e-7,"domain_scores_codex":[0.9983068,0.000008492225,0.0004784006,0.0003064357,0.0004629002,0.000437008],"domain_scores_gemma":[0.9931087,0.00006305765,0.0001757747,0.0004239315,0.005987037,0.0002414925],"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":[0.000002720823,0.000009511704,0.000230289,0.0001340946,0.000003175372,7.622332e-8,0.0007885073,0.00005462266,0.000003534578,0.02911302,0.1378472,0.8318132],"study_design_scores_gemma":[0.0003267797,0.00008411422,0.006783228,0.00003739954,0.000001458056,0.000002146174,0.0000107062,0.4435564,0.00005320515,0.0003587924,0.5486301,0.0001557238],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00385062,0.00003279595,0.975745,0.0001916504,0.009657401,0.0006048796,0.00002576689,0.0002327992,0.009659097],"genre_scores_gemma":[0.2129227,0.003295362,0.7137949,0.06075404,0.006595899,0.0006115278,0.0008820679,0.00004334238,0.001100092],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8316575,"threshold_uncertainty_score":0.9995848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02545232626805092,"score_gpt":0.2659466571246082,"score_spread":0.2404943308565573,"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."}}