{"id":"W4398524690","doi":"10.7910/dvn/pkjufn/tzkfc2","title":"FCC2001.002.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":[0.00006085969,0.0004480951,0.0004859617,0.0000976693,0.00006229996,0.0001120798,0.0006713523,0.0003687631,0.01705112],"category_scores_gemma":[0.00004169736,0.0004729003,0.0001383573,0.0001908241,0.00004652232,0.000168938,0.0001968565,0.0007400381,0.3363768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006908886,"about_ca_system_score_gemma":0.00002653289,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007484441,"about_ca_topic_score_gemma":0.00006557086,"domain_scores_codex":[0.998508,0.0000279504,0.000330762,0.0003987639,0.0002800591,0.0004544173],"domain_scores_gemma":[0.9985405,0.00004733771,0.00005866824,0.001070811,0.00002267055,0.000260007],"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":[0.00001007881,0.00001409827,4.283889e-7,0.0002454469,0.0001048395,0.0002227654,0.000009694813,0.002836731,0.0000200364,0.000006898097,0.9961486,0.0003803287],"study_design_scores_gemma":[0.0002643367,0.0000222828,0.000004579488,0.00008672813,0.0001026552,0.00001314556,0.00001516462,0.003896425,0.00002097306,0.000003640181,0.9950535,0.0005165515],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000006901583,0.000006300111,0.00008416845,0.00000430502,0.001736205,0.0001779367,0.9968026,0.0003705092,0.0008110365],"genre_scores_gemma":[0.00003398235,0.002065166,0.0001725132,0.0002963848,0.001431372,0.00001334256,0.995786,0.00007918526,0.0001220508],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3193257,"threshold_uncertainty_score":0.9997723,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01189696893874781,"score_gpt":0.1996204338375887,"score_spread":0.1877234648988409,"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."}}