{"id":"W4398365419","doi":"10.7910/dvn/pkjufn/6qfqdw","title":"FCC2001.042.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":[0.00006158121,0.0004479266,0.0004858336,0.00009779354,0.0000622902,0.0001120629,0.0006708652,0.000368592,0.01579664],"category_scores_gemma":[0.00004169657,0.0004726964,0.0001382619,0.0001910084,0.00004661076,0.000168183,0.000196713,0.000739424,0.3238952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006957637,"about_ca_system_score_gemma":0.00002737621,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007979012,"about_ca_topic_score_gemma":0.00006968431,"domain_scores_codex":[0.9985089,0.00002799737,0.0003305075,0.000398644,0.0002798081,0.0004540881],"domain_scores_gemma":[0.9985424,0.0000475144,0.00005863613,0.001068729,0.00002270366,0.0002599817],"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":[0.0000103528,0.00001398663,4.057339e-7,0.0002402102,0.0001047995,0.0002234376,0.000009383944,0.003224164,0.00002033859,0.000007520365,0.9957266,0.0004188281],"study_design_scores_gemma":[0.0002647788,0.00002215448,0.000004936244,0.00008574961,0.0001037424,0.00001315327,0.00001534973,0.003776128,0.00002161857,0.000003853883,0.9951721,0.0005164227],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000007408782,0.000005962645,0.0000805086,0.000004203381,0.0017651,0.0001747765,0.9967719,0.0003691229,0.0008209686],"genre_scores_gemma":[0.0000353225,0.001998426,0.0001736824,0.0002969551,0.001422272,0.00001335307,0.9958648,0.00007918648,0.0001160211],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3080985,"threshold_uncertainty_score":0.9997725,"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."}}