{"id":"W4398478665","doi":"10.7910/dvn/pkjufn/klruiy","title":"FCC2002.345.ran","year":2020,"lang":"ka","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":[0.000203972,0.00118218,0.001248073,0.0001433618,0.0002362314,0.0003825768,0.001598631,0.0009300968,0.06503034],"category_scores_gemma":[0.0001972562,0.001310289,0.000412268,0.0004715689,0.0001522546,0.0004713905,0.0007613376,0.001921716,0.7007456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002116962,"about_ca_system_score_gemma":0.00008638908,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001966641,"about_ca_topic_score_gemma":0.0001104297,"domain_scores_codex":[0.9956778,0.000128434,0.0009463365,0.001179035,0.0008608166,0.00120761],"domain_scores_gemma":[0.996262,0.0001903973,0.0002480088,0.00244137,0.00006624164,0.00079194],"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":[0.00008533312,0.00008754651,0.000004278329,0.0007739494,0.000443351,0.0009596731,0.00009859677,0.005969228,0.0001297142,0.00007166748,0.989819,0.001557667],"study_design_scores_gemma":[0.0009270664,0.000110245,0.00002271403,0.0004306103,0.0004690309,0.00004349171,0.0001518871,0.01723965,0.00006952901,0.000006546638,0.9791688,0.001360455],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005031393,0.00001979464,0.0004051662,0.00002714032,0.003918587,0.0005095807,0.9928368,0.0003850861,0.001847557],"genre_scores_gemma":[0.0007310493,0.0054052,0.0005818714,0.0008451472,0.00457916,0.00002566386,0.9870321,0.0002349073,0.000564947],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6357153,"threshold_uncertainty_score":0.9989347,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01395554336145621,"score_gpt":0.2068998217540985,"score_spread":0.1929442783926422,"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."}}