{"id":"W4398309968","doi":"10.7910/dvn/pkjufn/tzk3rx","title":"FCC2001.348.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":[0.00006369137,0.0004483858,0.0004868354,0.00009774774,0.000062356,0.0001122286,0.0006725138,0.000368741,0.01658034],"category_scores_gemma":[0.00004330259,0.0004728003,0.0001395828,0.0001890971,0.00004654977,0.0001684894,0.0001970705,0.0007392672,0.3398846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007131268,"about_ca_system_score_gemma":0.00002775219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000076576,"about_ca_topic_score_gemma":0.00006929526,"domain_scores_codex":[0.9984989,0.00002866218,0.0003321015,0.000399617,0.0002860376,0.0004546696],"domain_scores_gemma":[0.9985353,0.00004830958,0.00005892962,0.001074126,0.00002324309,0.0002600712],"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":[0.00001067362,0.00001400784,4.099766e-7,0.0002509264,0.0001050853,0.0002185261,0.000009748463,0.002907665,0.00002055473,0.000006824016,0.9960783,0.0003772776],"study_design_scores_gemma":[0.0002692082,0.0000223149,0.000004395531,0.00008726667,0.0001069813,0.00001324922,0.00001530878,0.003895178,0.00002160501,0.000003803608,0.9950441,0.000516557],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00000701847,0.000006463456,0.0000828538,0.000004273723,0.001773551,0.0001811511,0.9968367,0.0003682174,0.0007398137],"genre_scores_gemma":[0.00003437141,0.002085439,0.0001694992,0.000299597,0.001434891,0.00001332313,0.9957715,0.00007912485,0.0001122815],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.3233042,"threshold_uncertainty_score":0.9997724,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01184558204832753,"score_gpt":0.1998632451143943,"score_spread":0.1880176630660668,"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."}}