{"id":"W6950567355","doi":"10.5683/sp/jytigj","title":"Radio-Frequency Interference (RFI) Mitigation Algorithms in the Context of Fast Radio Burst (FRB) Searches","year":2017,"lang":"en","type":"dataset","venue":"Borealis","topic":"Geochemistry and Elemental Analysis","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Python (programming language); Context (archaeology); Metric (unit); Interference (communication); Electromagnetic interference","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001287341,0.002085294,0.001141193,0.002749342,0.0006997792,0.00160987,0.003365747,0.00195701,0.01328713],"category_scores_gemma":[0.005607547,0.0005485184,0.001437098,0.003289644,0.000532434,0.001259388,0.001746681,0.001614868,0.02117326],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001634993,"about_ca_system_score_gemma":0.00231002,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03724325,"about_ca_topic_score_gemma":0.1264136,"domain_scores_codex":[0.9989207,0.0001760498,0.0001237416,0.0003445637,0.0002862994,0.0001487323],"domain_scores_gemma":[0.9981347,0.000469936,0.000184839,0.0006087151,0.0004462654,0.0001555151],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001366812,0.00005017098,0.004134175,0.001061034,0.0001111685,0.00005740765,0.00005140368,0.002247216,0.0003467003,0.0007318924,0.983973,0.007099109],"study_design_scores_gemma":[0.0003320042,0.00004265623,0.01416123,0.0004694453,0.00008927145,0.0001668031,0.0001701636,0.005164266,0.001389876,0.003332922,0.9746119,0.00006924676],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000849679,0.0001660934,0.0003884501,0.0001084594,0.00004855427,0.00001885443,0.9962483,0.001385862,0.0007857044],"genre_scores_gemma":[0.00121166,0.00006287523,0.001042268,0.00003814499,0.000005628334,0.00004556063,0.9970852,0.0001052509,0.0004034368],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.03724325,"threshold_uncertainty_score":0.07405293,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02523891399657967,"score_gpt":0.2559843235255411,"score_spread":0.2307454095289614,"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."}}