{"id":"W4236570005","doi":"10.5539/cis.v11n3p123","title":"Reviewer Acknowledgements for Computer and Information Science, Vol. 11, No. 3","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; 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":[0.03785913,0.002692827,0.006098565,0.01017565,0.005328669,0.01028057,0.00537093,0.01530413,0.1308116],"category_scores_gemma":[0.3996433,0.00162061,0.004360051,0.004732228,0.002824625,0.006125866,0.003624023,0.0094592,0.07648178],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005713341,"about_ca_system_score_gemma":0.01046002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003703097,"about_ca_topic_score_gemma":0.005588147,"domain_scores_codex":[0.9538482,0.007592612,0.009151022,0.003242802,0.02425208,0.001913144],"domain_scores_gemma":[0.2170376,0.02563062,0.01130311,0.006742241,0.7302219,0.009064499],"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":[0.00002775385,0.000003994126,0.0000897045,0.0003478506,0.000008204047,0.00006659855,0.00003064005,0.0000105528,0.00003844266,0.0001421375,0.9943334,0.00490069],"study_design_scores_gemma":[0.0001669378,0.00003875662,0.0008528929,0.002390661,0.00008303835,0.001011704,0.0002789242,0.0003085049,0.0002946305,0.001629317,0.9928312,0.0001134153],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"other","genre_scores_codex":[0.0001689115,0.003363633,0.001473288,0.1206814,0.8668258,0.0007416273,0.0007368316,0.0005220071,0.00548652],"genre_scores_gemma":[0.006655272,0.009447603,0.003800432,0.1576092,0.715671,0.003265627,0.001903588,0.001531661,0.1001155],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.1308116,"threshold_uncertainty_score":0.4376085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02160252724951813,"score_gpt":0.2623329399896102,"score_spread":0.240730412740092,"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."}}