{"id":"W4288967721","doi":"10.5539/nct.v7n1p61","title":"Reviewer Acknowledgements for Network and Communication Technologies Vol. 7, No. 1","year":2022,"lang":"en","type":"article","venue":"Network and Communication Technologies","topic":"Internet of Things and AI","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Library science; Telecommunications; Computer 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"],"consensus_categories":[],"category_scores_codex":[0.001036565,0.0001965264,0.0002806224,0.00009212711,0.001512842,0.0002095406,0.003206083,0.0001404559,0.0000139318],"category_scores_gemma":[0.001964866,0.0001873216,0.00004437461,0.0004790397,0.0003186832,0.000336935,0.00743316,0.0005205531,0.00001271585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005578066,"about_ca_system_score_gemma":0.00001847446,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007000789,"about_ca_topic_score_gemma":0.00001308026,"domain_scores_codex":[0.9986102,0.0001445836,0.0003574691,0.0003660078,0.0001606708,0.0003610817],"domain_scores_gemma":[0.9957659,0.000284021,0.0003012221,0.002117231,0.001513016,0.00001866941],"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":[0.00001038029,0.00004588416,0.0006052874,0.00003889893,0.00003655938,1.574005e-7,0.0001353017,0.0001591578,0.000006820075,0.07255266,0.5969934,0.3294155],"study_design_scores_gemma":[0.0002595231,0.0002147854,0.0001450243,0.0001214691,0.00001511101,0.000001815849,0.000482905,0.01647544,0.00005570445,0.1451812,0.8368099,0.0002371505],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"review","genre_gemma":"methods","genre_scores_codex":[0.008230717,0.7326145,0.1696668,0.04626959,0.01079722,0.005753292,0.00003230517,0.0169017,0.009733825],"genre_scores_gemma":[0.3950304,0.1203782,0.4756164,0.00147423,0.0003669404,0.003280505,0.00009860637,0.0000611013,0.003693671],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.6122363,"threshold_uncertainty_score":0.999787,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0169485484250699,"score_gpt":0.2537134207704629,"score_spread":0.236764872345393,"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."}}