{"id":"W4398365977","doi":"10.7910/dvn/pkjufn/rfptg1","title":"FCC2001.241.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":[0.00006113873,0.0004484156,0.0004860493,0.00009771311,0.00006277709,0.0001124527,0.0006732238,0.0003693674,0.01650701],"category_scores_gemma":[0.00004226889,0.0004691027,0.0001397301,0.0001894953,0.00004625459,0.000169137,0.0001978344,0.0007404735,0.3317997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000696596,"about_ca_system_score_gemma":0.00002718577,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007741238,"about_ca_topic_score_gemma":0.00006669812,"domain_scores_codex":[0.9985075,0.0000277413,0.0003306247,0.0003990651,0.0002801758,0.000454865],"domain_scores_gemma":[0.9985409,0.00004671343,0.0000587711,0.001070609,0.00002272508,0.0002602368],"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":[0.00001028163,0.00001397467,4.028956e-7,0.0002452972,0.0001043545,0.0002236709,0.000009680154,0.002858054,0.00002104812,0.000006936368,0.9961053,0.000400969],"study_design_scores_gemma":[0.0002647575,0.00002244209,0.000004459057,0.00008707814,0.0001029157,0.00001328248,0.00001538168,0.003721556,0.00002212326,0.000003813185,0.9952239,0.0005183265],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000006593895,0.000005928858,0.00008368809,0.000004345762,0.001748411,0.0001791764,0.9968031,0.000380292,0.0007884311],"genre_scores_gemma":[0.00003304982,0.001951475,0.0001724259,0.0003000675,0.001413604,0.00001351435,0.9959182,0.00008060715,0.0001170607],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3152927,"threshold_uncertainty_score":0.9997761,"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."}}