{"id":"W4398323082","doi":"10.7910/dvn/pkjufn/tclmut","title":"FCC2002.360.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":[0.00006172652,0.0004412917,0.0004777195,0.000062433,0.00006144065,0.0001113056,0.0006657226,0.0003566132,0.01521193],"category_scores_gemma":[0.00004724637,0.0004650926,0.000138123,0.0001777941,0.00004536665,0.0001644296,0.0001978069,0.0007312826,0.2819847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006843844,"about_ca_system_score_gemma":0.00002114742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004807951,"about_ca_topic_score_gemma":0.00006431277,"domain_scores_codex":[0.9984729,0.00002751669,0.0003263902,0.0003917465,0.0003427294,0.0004386962],"domain_scores_gemma":[0.998563,0.00005001029,0.0000576936,0.001057829,0.00001947789,0.0002520198],"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":[0.00001045281,0.0000136798,5.539739e-7,0.0002423002,0.0001038999,0.0002127604,0.000009273544,0.002020401,0.0000218303,0.000005746366,0.9967954,0.0005637488],"study_design_scores_gemma":[0.0002519072,0.0000221774,0.000004042982,0.00008445718,0.0001034855,0.00001228978,0.00001509852,0.004939629,0.00002738053,0.000003142589,0.9940283,0.0005080703],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000006489452,0.000006147548,0.0000915869,0.000003916962,0.001671608,0.0001720748,0.9968886,0.0003440626,0.0008155441],"genre_scores_gemma":[0.00004781638,0.001577323,0.0001724548,0.0002938982,0.001382522,0.00001334768,0.9963015,0.00007824047,0.0001329225],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2667728,"threshold_uncertainty_score":0.9997801,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01186699563184929,"score_gpt":0.19833779110899,"score_spread":0.1864707954771407,"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."}}