{"id":"W4398711895","doi":"10.7910/dvn/pkjufn/bn8zo9","title":"FCC2002.331.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":[0.00006148336,0.0004412176,0.0004771021,0.00006247003,0.00006135598,0.0001108325,0.0006636085,0.0003593623,0.01570241],"category_scores_gemma":[0.00004594539,0.0004649284,0.0001378772,0.000176202,0.00004536013,0.0001642175,0.0001965865,0.0007161045,0.2842929],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006772749,"about_ca_system_score_gemma":0.00002109488,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004908223,"about_ca_topic_score_gemma":0.00006301024,"domain_scores_codex":[0.9984781,0.00002751872,0.0003257568,0.0003876684,0.0003424447,0.0004385084],"domain_scores_gemma":[0.9985663,0.00004936431,0.00005758208,0.001055595,0.00001942071,0.00025178],"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":[0.00001034292,0.00001369258,4.540084e-7,0.0002434739,0.0001010384,0.0002171726,0.000009717339,0.002339718,0.00002191211,0.000006038472,0.9965419,0.000494579],"study_design_scores_gemma":[0.0002534435,0.00002214246,0.000004845993,0.00008432544,0.0001026914,0.00001252563,0.00001611027,0.003743327,0.00002779074,0.00000301849,0.9952212,0.0005085939],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000006893185,0.000005495223,0.00009296484,0.000003968487,0.001695623,0.0001722087,0.9968551,0.0003423812,0.0008253027],"genre_scores_gemma":[0.0000442941,0.001658712,0.0001716971,0.0002888409,0.001388316,0.00001339046,0.9962319,0.00007821574,0.000124595],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2685905,"threshold_uncertainty_score":0.9997802,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01187632136744047,"score_gpt":0.1983757581922939,"score_spread":0.1864994368248535,"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."}}