{"id":"W4398593738","doi":"10.7910/dvn/pkjufn/4uutsi","title":"FCC2001.096.ran","year":2020,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Wireless Sensor Networks and IoT","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Ran; Computer science; Computer network","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00006155412,0.0004484546,0.000487387,0.0001002613,0.00006241287,0.0001099224,0.0006694354,0.0003706917,0.01589589],"category_scores_gemma":[0.00004286868,0.0004722404,0.0001391146,0.00019551,0.00004661724,0.0001682228,0.0001964246,0.0007411953,0.3275855],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006894628,"about_ca_system_score_gemma":0.00002698278,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008036778,"about_ca_topic_score_gemma":0.00006814708,"domain_scores_codex":[0.998509,0.00002832837,0.0003317165,0.0003982588,0.0002792272,0.0004534425],"domain_scores_gemma":[0.9985459,0.00004741406,0.00005897673,0.001064333,0.00002256736,0.0002608531],"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":[0.00001019308,0.00001388931,4.319959e-7,0.0002429682,0.0001053294,0.0002198065,0.000009992253,0.002921812,0.00002011046,0.000006957194,0.9961012,0.0003473325],"study_design_scores_gemma":[0.0002592687,0.00002174139,0.000004517676,0.00008692714,0.0001032249,0.00001287598,0.000015963,0.003711117,0.0000211416,0.000003771218,0.9952436,0.0005158248],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000007531824,0.000005810621,0.0000828871,0.000004280757,0.0017824,0.000177906,0.9968036,0.0003703754,0.0007651698],"genre_scores_gemma":[0.00003511162,0.001961209,0.0001703302,0.0002897613,0.001439224,0.00001285099,0.9958923,0.00007839133,0.0001207872],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3116896,"threshold_uncertainty_score":0.9997729,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01184009217885027,"score_gpt":0.1998802100570442,"score_spread":0.188040117878194,"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."}}