{"id":"W4398547033","doi":"10.7910/dvn/pkjufn/gfv9qb","title":"FCC2002.309.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":[0.00005788437,0.000368437,0.0004861747,0.0001015829,0.00004186596,0.00003535411,0.0006980587,0.0005210147,0.009887616],"category_scores_gemma":[0.00002390496,0.0003886169,0.0001153528,0.000172893,0.0000490331,0.0001122337,0.0000896706,0.0006480662,0.2380224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005127772,"about_ca_system_score_gemma":0.00002262448,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001033996,"about_ca_topic_score_gemma":0.0002376673,"domain_scores_codex":[0.9986828,0.00001232499,0.0003515864,0.0003622216,0.0002434873,0.0003475556],"domain_scores_gemma":[0.9986386,0.00001995858,0.00005465034,0.001129438,0.00001353401,0.0001437912],"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":[0.000005102499,0.0000111899,0.000002472697,0.0004354304,0.0001125555,0.0003742347,0.000008449291,0.00004298528,0.00003746253,0.00002865139,0.9986267,0.0003147776],"study_design_scores_gemma":[0.0002635061,0.00002205484,0.00001314693,0.00006744567,0.00009577772,0.00002506364,0.0000169469,0.00007207494,0.00005046422,0.000006872837,0.9989783,0.0003884155],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000006695549,0.000004369537,0.0002522146,0.000003977747,0.001292531,0.0002048937,0.997016,0.0007907918,0.0004285619],"genre_scores_gemma":[0.0001833796,0.0004067495,0.0001638742,0.00008497338,0.0003222978,0.00003174659,0.9986827,0.0000569382,0.00006732419],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2281348,"threshold_uncertainty_score":0.9998566,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01031191441678804,"score_gpt":0.1907338716552845,"score_spread":0.1804219572384964,"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."}}