{"id":"W4398283423","doi":"10.7910/dvn/pkjufn/lfidxc","title":"FCC2001.295.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":[0.00006038582,0.0004483071,0.0004847724,0.00009954572,0.0000624462,0.0001122328,0.0006722505,0.0003773905,0.01709418],"category_scores_gemma":[0.00004154049,0.0004730909,0.0001398591,0.0001920096,0.00004664824,0.0001685268,0.0001936883,0.0007548042,0.3288787],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006769997,"about_ca_system_score_gemma":0.00002750028,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007593332,"about_ca_topic_score_gemma":0.00006537129,"domain_scores_codex":[0.9985078,0.00002794454,0.0003306976,0.0003988191,0.0002800452,0.0004546885],"domain_scores_gemma":[0.9985415,0.00004730468,0.00005865784,0.0010697,0.00002267332,0.0002601745],"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":[0.00001059054,0.00001410522,3.917891e-7,0.0002420069,0.0001074929,0.0002265527,0.000009695709,0.00296745,0.00002044374,0.000007014211,0.9960055,0.000388749],"study_design_scores_gemma":[0.0002761972,0.00002256392,0.000004196549,0.00008829996,0.0001062751,0.00001331845,0.00001629718,0.003749558,0.0000217298,0.000003745019,0.995181,0.0005168234],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000006347037,0.000006216846,0.00008609272,0.000004352623,0.001780014,0.000178432,0.9966812,0.000380253,0.0008770493],"genre_scores_gemma":[0.00003417965,0.00208981,0.0001697275,0.0003076405,0.001433893,0.00001336504,0.9957559,0.00008056816,0.0001149305],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3117846,"threshold_uncertainty_score":0.9997721,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01184558204832753,"score_gpt":0.1998632451143943,"score_spread":0.1880176630660668,"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."}}