{"id":"W4398604523","doi":"10.7910/dvn/pkjufn/fpzpbh","title":"FCC2001.060.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":[0.00006143274,0.0004478108,0.0004854474,0.00009723655,0.00006228445,0.0001089619,0.0006724783,0.0003644213,0.01666337],"category_scores_gemma":[0.00004222496,0.0004725358,0.0001388896,0.0001914131,0.00004622695,0.0001681982,0.0001977907,0.0007382179,0.331046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000668582,"about_ca_system_score_gemma":0.00002718903,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007614628,"about_ca_topic_score_gemma":0.00006806188,"domain_scores_codex":[0.9985084,0.00002794316,0.0003321888,0.0003988317,0.0002795013,0.0004531581],"domain_scores_gemma":[0.998539,0.0000464493,0.00005852061,0.001070056,0.00002278326,0.0002631303],"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":[0.00001017451,0.00001400696,4.020407e-7,0.0002425452,0.0001048704,0.000219327,0.000009653551,0.003179671,0.00002629926,0.00000670731,0.995828,0.0003583564],"study_design_scores_gemma":[0.0002630506,0.00002195033,0.000004243595,0.00008465454,0.0001037639,0.00001289143,0.00001540197,0.003013283,0.00002672707,0.000003848407,0.9959335,0.0005167047],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00000667843,0.000006070111,0.00008889256,0.000004231016,0.001830329,0.0001786014,0.9967239,0.0003709181,0.000790406],"genre_scores_gemma":[0.00003429034,0.002068445,0.0001697053,0.0003007303,0.001436937,0.00001337826,0.995779,0.00007914841,0.0001183251],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3143826,"threshold_uncertainty_score":0.9997726,"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."}}