{"id":"W4398612437","doi":"10.7910/dvn/pkjufn/wdvod8","title":"FCC2002.067.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":[0.00006228329,0.0004411997,0.0004773937,0.0000623823,0.0000619686,0.0001107835,0.0006627991,0.0003592045,0.01603596],"category_scores_gemma":[0.00004806658,0.0004649978,0.0001380583,0.0001772114,0.00004498166,0.0001641338,0.0001965574,0.0007363283,0.28726],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006859902,"about_ca_system_score_gemma":0.00002105778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004663436,"about_ca_topic_score_gemma":0.00005838679,"domain_scores_codex":[0.9984739,0.00002793688,0.0003258385,0.0003914895,0.0003423324,0.0004385402],"domain_scores_gemma":[0.9985636,0.00005067346,0.00005758155,0.001056776,0.00001941571,0.0002519065],"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":[0.0000104308,0.00001367978,4.77039e-7,0.0002435058,0.0001012487,0.0002129693,0.000009609076,0.002377888,0.00002255004,0.000005812746,0.9964676,0.0005341878],"study_design_scores_gemma":[0.0002532365,0.00002243535,0.000004793843,0.00008493021,0.000102696,0.00001246588,0.00001541723,0.003936642,0.00002889495,0.000002901042,0.9950271,0.0005084662],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000007238369,0.000005400388,0.00009081165,0.000003824357,0.00165307,0.0001722334,0.9968873,0.0003360952,0.0008440687],"genre_scores_gemma":[0.0000459725,0.001629156,0.0001725869,0.0002808412,0.001385813,0.00001336918,0.9962685,0.00007810989,0.0001256444],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.271224,"threshold_uncertainty_score":0.9997802,"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."}}