{"id":"W4398320176","doi":"10.7910/dvn/pkjufn/5lkfxn","title":"FCC2002.044.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":[0.00006148606,0.0004415325,0.0004781182,0.00006248475,0.00006147966,0.0001113342,0.0006642205,0.0003595528,0.01540283],"category_scores_gemma":[0.00004783078,0.0004652797,0.0001381511,0.0001778583,0.00004515333,0.0001645466,0.0001970699,0.0007309532,0.2823009],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006874261,"about_ca_system_score_gemma":0.00002119563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004793465,"about_ca_topic_score_gemma":0.00006270219,"domain_scores_codex":[0.9984724,0.00002747712,0.0003264035,0.0003915029,0.0003430402,0.0004391756],"domain_scores_gemma":[0.9985634,0.00004999831,0.00005767723,0.001057316,0.00001947096,0.0002521081],"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":[0.0000105236,0.00001369783,4.598824e-7,0.0002424136,0.0001025573,0.0002133516,0.000009598218,0.002420824,0.00002226329,0.00000621924,0.9964603,0.0004978112],"study_design_scores_gemma":[0.0002540431,0.00002230658,0.000004609351,0.00008448334,0.000102714,0.00001233881,0.00001558407,0.003879574,0.00002830575,0.000003147447,0.995084,0.0005088209],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000006785034,0.000005471675,0.00009390738,0.000003950881,0.001670911,0.0001724575,0.996861,0.0003426758,0.0008428625],"genre_scores_gemma":[0.00004459285,0.001602454,0.0001729391,0.0002852353,0.001388551,0.0000133724,0.9962915,0.00007827034,0.000123107],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2668981,"threshold_uncertainty_score":0.9997799,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01186855000602602,"score_gpt":0.1982685848667247,"score_spread":0.1864000348606986,"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."}}