{"id":"W4252653364","doi":"10.5539/cis.v10n4p81","title":"Reviewer Acknowledgements for Computer and Information Science, Vol. 10, No. 4","year":2017,"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; 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":["sts","scholarly_communication"],"consensus_categories":["scholarly_communication"],"category_scores_codex":[0.001423815,0.0001591403,0.000177924,0.0004461863,0.001727557,0.007723286,0.001985074,0.00003851608,0.00001264189],"category_scores_gemma":[0.001497569,0.0001346791,0.00003136618,0.0003859,0.001013313,0.1354685,0.001953891,0.00006421564,0.0006408644],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004423254,"about_ca_system_score_gemma":0.0002491982,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000232699,"about_ca_topic_score_gemma":3.167138e-7,"domain_scores_codex":[0.9984456,0.000006475783,0.0004453575,0.0003062408,0.0004162789,0.0003801023],"domain_scores_gemma":[0.9910864,0.00003722934,0.0003422385,0.000798323,0.007485264,0.0002504968],"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":[0.000004154921,0.00001272387,0.0003467814,0.0001068744,0.000003306742,6.661724e-8,0.0005112265,0.00001361582,0.000003013964,0.02935238,0.06384353,0.9058023],"study_design_scores_gemma":[0.0004314375,0.0001009613,0.01476989,0.00004748419,0.000001918955,0.00000250175,0.000004197337,0.3600188,0.00006407743,0.0002578276,0.6241267,0.0001741358],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002543061,0.0000376325,0.9622963,0.0002095975,0.009675403,0.0005759995,0.00002272098,0.00008422457,0.02455503],"genre_scores_gemma":[0.1731646,0.001043791,0.7974156,0.02276124,0.004205875,0.0002288407,0.0001657076,0.00002011196,0.0009942214],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9056282,"threshold_uncertainty_score":0.999572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02843096815004034,"score_gpt":0.2761180709127785,"score_spread":0.2476871027627382,"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."}}