{"id":"W4386291874","doi":"10.5539/cis.v16n3p36","title":"Reviewer Acknowledgements for Computer and Information Science, Vol. 16, No. 3","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; 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":[0.001638461,0.000154576,0.0001688139,0.000893368,0.0006999598,0.002999682,0.001110302,0.00003698598,0.000007204936],"category_scores_gemma":[0.0008805501,0.0001328657,0.0000310251,0.002155636,0.0005738584,0.08420359,0.001442198,0.00006686913,0.001213783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000606561,"about_ca_system_score_gemma":0.0002417255,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001622004,"about_ca_topic_score_gemma":2.602167e-7,"domain_scores_codex":[0.9983064,0.000008487915,0.0004784009,0.0003065118,0.0004630693,0.0004371099],"domain_scores_gemma":[0.9930555,0.00006332301,0.0001755961,0.0004240603,0.006040053,0.0002414987],"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":[0.000002768601,0.000009588668,0.0002385218,0.000136072,0.000003199291,7.593643e-8,0.0007944822,0.00005487423,0.000003673205,0.02880577,0.136307,0.833644],"study_design_scores_gemma":[0.0003287883,0.0000840472,0.006841403,0.00003772668,0.000001452341,0.000002127164,0.00001075825,0.4455388,0.00005443496,0.0003575298,0.5465869,0.0001560737],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003870274,0.00003231564,0.9759482,0.0001905255,0.009626456,0.0006019759,0.00002574412,0.0002311602,0.009473313],"genre_scores_gemma":[0.2153849,0.003231211,0.7121699,0.06009238,0.006511987,0.000605454,0.000858045,0.00004294483,0.001103146],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8334879,"threshold_uncertainty_score":0.9995639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02590928516141665,"score_gpt":0.2661037771280502,"score_spread":0.2401944919666335,"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."}}