{"id":"W4398320176","doi":"10.7910/dvn/pkjufn/5lkfxn","title":"FCC2002.044.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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0009999312,0.003201363,0.001600976,0.003695587,0.001052112,0.00303994,0.003734588,0.002942407,0.08471444],"category_scores_gemma":[0.005637421,0.0007255545,0.001707003,0.006466911,0.0005335319,0.001730934,0.001946207,0.001703047,0.1461995],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001630601,"about_ca_system_score_gemma":0.002264867,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04146505,"about_ca_topic_score_gemma":0.06600848,"domain_scores_codex":[0.9988897,0.0001645697,0.0001122677,0.0003186525,0.0002471695,0.0002675485],"domain_scores_gemma":[0.9978215,0.0004083033,0.0001749822,0.0006565253,0.0006467896,0.000291877],"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":[0.00004808612,0.00001162701,0.0002768186,0.0002293669,0.00001443199,0.000009805895,0.000006759506,0.0002390563,0.00004831195,0.000213178,0.997835,0.001067545],"study_design_scores_gemma":[0.0004043938,0.00003898867,0.003527778,0.0002765609,0.00003641568,0.00006241064,0.00008500686,0.00129394,0.0004066911,0.001670056,0.9921569,0.00004085058],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00009185269,0.00005056431,0.00003567387,0.00006477527,0.00003412203,0.000006079682,0.9986095,0.0004321919,0.0006751779],"genre_scores_gemma":[0.0003389899,0.00003898737,0.0001158811,0.00004369456,0.00001173679,0.00002394039,0.9988795,0.00006425184,0.0004830264],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9152856,"threshold_uncertainty_score":0.283398,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01186855000602602,"score_gpt":0.1982685848667247,"score_spread":0.1864000348606986,"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."}}