{"id":"W4398384367","doi":"10.7910/dvn/pkjufn/qgfoug","title":"FCC2002.153.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":[0.00005833635,0.0003700022,0.0004894131,0.0001019026,0.00004215451,0.00003552237,0.0007013468,0.000527301,0.01033038],"category_scores_gemma":[0.00002501239,0.0003900554,0.0001157293,0.0001734986,0.00005051963,0.000112865,0.00009015168,0.0006544332,0.2447569],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005362419,"about_ca_system_score_gemma":0.0000232591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001078836,"about_ca_topic_score_gemma":0.0002440001,"domain_scores_codex":[0.9986757,0.00001234038,0.0003533577,0.0003646369,0.0002445236,0.00034946],"domain_scores_gemma":[0.9986301,0.000020287,0.0000544128,0.001136645,0.00001373625,0.0001448128],"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":[0.000004986262,0.00001078103,0.000002813875,0.0004457502,0.0001111981,0.0003818854,0.000008682729,0.00004558978,0.00004047437,0.00003052078,0.9986053,0.0003120124],"study_design_scores_gemma":[0.0002529024,0.000024066,0.00001382435,0.00006948467,0.0000951636,0.00002596292,0.00001626063,0.00007223162,0.00004591617,0.000007256461,0.9989871,0.0003898085],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000009399845,0.00000458765,0.0001837621,0.000003967607,0.001281752,0.0002054732,0.9971007,0.0007824448,0.0004278801],"genre_scores_gemma":[0.0001849162,0.0004275616,0.0001577349,0.00008957689,0.0003239051,0.00003176161,0.9986562,0.00005729801,0.00007108247],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2344265,"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."}}