{"id":"W4398387192","doi":"10.7910/dvn/pkjufn/lvkotv","title":"FCC2001.071.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":[0.00006154802,0.0004484484,0.0004866703,0.00009770945,0.00006240069,0.0001120645,0.0006719776,0.0003690986,0.01602138],"category_scores_gemma":[0.00004179569,0.0004731819,0.0001384458,0.000190884,0.00004659491,0.0001690681,0.0001972309,0.0007405618,0.333608],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006967553,"about_ca_system_score_gemma":0.00002743828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007599968,"about_ca_topic_score_gemma":0.00006648964,"domain_scores_codex":[0.9985074,0.00002798464,0.0003309759,0.0003987475,0.0002800475,0.0004548765],"domain_scores_gemma":[0.9985396,0.00004738187,0.00005868588,0.001071409,0.00002272228,0.0002602222],"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":[0.00001025391,0.00001394678,4.541896e-7,0.0002432064,0.000104989,0.0002236583,0.000007991395,0.002845908,0.00002072865,0.000007138121,0.9961663,0.0003554279],"study_design_scores_gemma":[0.0002651582,0.00002215008,0.000004686342,0.00008614887,0.0001038347,0.00001314741,0.00001553447,0.003690823,0.00002150879,0.000003330852,0.9952567,0.0005170058],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000006900788,0.000006041354,0.00008552343,0.000004231822,0.001749622,0.0001785857,0.9967855,0.0003707863,0.0008127803],"genre_scores_gemma":[0.00003425132,0.002010522,0.0001730284,0.0002681192,0.001420884,0.00001336427,0.9958795,0.00007917477,0.0001211244],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3175866,"threshold_uncertainty_score":0.999772,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0118495727525685,"score_gpt":0.1999503156488169,"score_spread":0.1881007428962485,"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."}}