{"id":"W4398622860","doi":"10.7910/dvn/pkjufn/pkenqy","title":"FCC2001.332.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":[0.00005850489,0.000376,0.0004990941,0.0001595411,0.000042842,0.00003584425,0.0007101404,0.0005416251,0.0104938],"category_scores_gemma":[0.00002164624,0.0003969051,0.0001172684,0.000184997,0.00005222358,0.0001161488,0.00009031541,0.0006617345,0.2816463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005236392,"about_ca_system_score_gemma":0.00002909737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001739939,"about_ca_topic_score_gemma":0.0002712239,"domain_scores_codex":[0.9986941,0.00001258693,0.0003595235,0.000371708,0.0002000097,0.0003620578],"domain_scores_gemma":[0.9986125,0.00001493136,0.00005557497,0.00115144,0.0000160147,0.0001495492],"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":[0.000005002774,0.00001137365,0.000002690658,0.000447591,0.0001129957,0.0004015792,0.000008783254,0.00004883099,0.00004829937,0.00003750978,0.9986483,0.0002270379],"study_design_scores_gemma":[0.0002686981,0.00002249232,0.00001471708,0.0000708934,0.00009673347,0.00002809622,0.00001591151,0.00006858268,0.00003653941,0.000008917942,0.9989722,0.000396237],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00001018575,0.000004862164,0.000168056,0.00000443641,0.001389988,0.0002127381,0.9969547,0.0008483764,0.0004066863],"genre_scores_gemma":[0.0001718559,0.0005243761,0.0001556874,0.00009541161,0.0003368188,0.00003175311,0.9985611,0.00005809802,0.0000649245],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2711525,"threshold_uncertainty_score":0.9998483,"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."}}