{"id":"W4398473179","doi":"10.7910/dvn/pkjufn/vvjttm","title":"FCC2001.355.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":[0.00005750712,0.0003756116,0.000495113,0.0001625261,0.00004266364,0.00003583053,0.0007096111,0.000553915,0.01126999],"category_scores_gemma":[0.00002170084,0.0003965866,0.0001171388,0.0001874009,0.00005214187,0.0001155985,0.00008866741,0.000674469,0.2860684],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005038655,"about_ca_system_score_gemma":0.00002878176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001692918,"about_ca_topic_score_gemma":0.0002583793,"domain_scores_codex":[0.9986966,0.00001255925,0.0003579701,0.000371337,0.0001997155,0.0003618058],"domain_scores_gemma":[0.9986102,0.00001917184,0.00005534033,0.001149835,0.00001601136,0.0001494423],"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":[0.000005009232,0.0000114335,0.00000241582,0.0004454797,0.00011592,0.0004065074,0.000008748901,0.00005479663,0.00003850491,0.00003566298,0.99865,0.0002254932],"study_design_scores_gemma":[0.0002729378,0.00002261621,0.00001253148,0.00007242458,0.00009926019,0.00002831209,0.00001685414,0.00006802689,0.00003584467,0.000008816876,0.9989665,0.0003958739],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000008888793,0.000005011284,0.0001669542,0.000004509179,0.001387297,0.0002123228,0.9969437,0.0008432657,0.000428023],"genre_scores_gemma":[0.00014042,0.000552765,0.0001543559,0.00009289207,0.0003300571,0.00003171266,0.9985717,0.00005781835,0.00006825718],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2747984,"threshold_uncertainty_score":0.9998486,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01028644552546442,"score_gpt":0.1922603851564491,"score_spread":0.1819739396309847,"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."}}