{"id":"W4398462297","doi":"10.7910/dvn/pkjufn/hbbqss","title":"FCC2001.026.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":[0.00006054562,0.0004472111,0.0004852414,0.00009767953,0.00006237972,0.0001133316,0.0006735612,0.0003693548,0.01639625],"category_scores_gemma":[0.00004121847,0.0004720073,0.0001381871,0.0001900223,0.00004653791,0.000170362,0.0001988495,0.0007399637,0.34029],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006958509,"about_ca_system_score_gemma":0.00002699432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007733442,"about_ca_topic_score_gemma":0.00006363139,"domain_scores_codex":[0.9985113,0.00002776995,0.0003300927,0.0003982872,0.0002796465,0.0004529278],"domain_scores_gemma":[0.998542,0.0000470336,0.00005863963,0.001069936,0.00002268707,0.0002597159],"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":[0.00001024359,0.00001395585,4.213475e-7,0.0002401299,0.0001047729,0.0002232939,0.00000958463,0.00291348,0.00002050317,0.000006945263,0.996069,0.0003876573],"study_design_scores_gemma":[0.0002634051,0.00002226812,0.000004568599,0.00008597557,0.0001037017,0.00001293383,0.00001531226,0.003723895,0.00002098067,0.000003687098,0.9952276,0.0005157219],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000006733588,0.000006118452,0.00008680281,0.000004205088,0.001769056,0.0001775499,0.9967477,0.0003814117,0.0008203875],"genre_scores_gemma":[0.00003370605,0.001992072,0.0001738055,0.000301705,0.001426159,0.00001288262,0.9958595,0.00008155998,0.0001186052],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3238938,"threshold_uncertainty_score":0.9997731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01184896424148209,"score_gpt":0.200025994117049,"score_spread":0.1881770298755669,"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."}}