{"id":"W4398632515","doi":"10.7910/dvn/pkjufn/ce1stf","title":"FCC2002.080.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":[0.0000617103,0.0004415434,0.0004780584,0.00006238789,0.00006142778,0.0001113953,0.0006652472,0.0003595808,0.01545122],"category_scores_gemma":[0.00004892025,0.0004652784,0.0001381415,0.0001776768,0.00004515262,0.0001646088,0.0001972341,0.0007311639,0.2827399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006859688,"about_ca_system_score_gemma":0.00002123452,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004791965,"about_ca_topic_score_gemma":0.00006174375,"domain_scores_codex":[0.9984719,0.00002750968,0.0003265619,0.0003920013,0.0003428439,0.0004392068],"domain_scores_gemma":[0.998561,0.00005088262,0.00005786098,0.001058708,0.00001945057,0.0002520801],"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":[0.00001049478,0.00001368711,4.516552e-7,0.0002430057,0.0001025572,0.0002131956,0.000009587397,0.002420069,0.0000221213,0.000006021538,0.9964359,0.0005229],"study_design_scores_gemma":[0.0002533819,0.00002236458,0.000004689025,0.00008448586,0.0001026287,0.00001232972,0.00001547191,0.003879374,0.00002819012,0.000003067232,0.9950852,0.000508828],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000006668491,0.000005590625,0.0000936674,0.000003994001,0.001655616,0.0001726569,0.9968995,0.0003427829,0.0008194533],"genre_scores_gemma":[0.00004406228,0.001636319,0.0001733648,0.0002841829,0.001389108,0.00001340393,0.996258,0.00007827007,0.0001232919],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2672887,"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."}}