{"id":"W4398556349","doi":"10.7910/dvn/pkjufn/d0wyda","title":"FCC2002.127.ran","year":2020,"lang":"en","type":"dataset","venue":"Harvard Dataverse","topic":"Transport Systems and Technology","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":[0.00005839071,0.0003699323,0.0004893019,0.0001018823,0.00004215585,0.00003549718,0.0007009837,0.0005271686,0.01039779],"category_scores_gemma":[0.00002502112,0.0003899767,0.0001157184,0.0001734885,0.00005044447,0.0001128099,0.00009008987,0.0006525444,0.2472345],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005153245,"about_ca_system_score_gemma":0.00002257361,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001045836,"about_ca_topic_score_gemma":0.0002382069,"domain_scores_codex":[0.9986761,0.00001234392,0.0003532843,0.0003643886,0.0002444506,0.0003494099],"domain_scores_gemma":[0.9986313,0.00002031292,0.00005440656,0.001135466,0.00001373327,0.0001447845],"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":[0.000005076882,0.00001112021,0.00000274974,0.0004539206,0.000110925,0.0003881225,0.000008561319,0.0000438464,0.00004271164,0.0000313774,0.9986064,0.000295174],"study_design_scores_gemma":[0.0002574713,0.00002228028,0.00001350678,0.00006998807,0.0000961993,0.00002638967,0.00001598819,0.00007043753,0.00004775461,0.000007315524,0.9989829,0.0003897437],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000009458217,0.000004513147,0.0001858583,0.000004102119,0.001304585,0.0002070523,0.9970806,0.0007827152,0.0004211684],"genre_scores_gemma":[0.0001797778,0.0004264763,0.0001578759,0.00008962786,0.0003233113,0.0000324969,0.9986634,0.00005729512,0.00006977678],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2368367,"threshold_uncertainty_score":0.9998552,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01030042744879746,"score_gpt":0.1905832209160307,"score_spread":0.1802827934672333,"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."}}