{"id":"W4398481972","doi":"10.7910/dvn/pkjufn/yl12xj","title":"FCC2001.306.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":[0.0000579028,0.000376001,0.0004982931,0.0001595654,0.0000428673,0.00003584031,0.0007104014,0.0005414327,0.0107541],"category_scores_gemma":[0.00002187236,0.0003969207,0.0001173472,0.0001850315,0.0000522399,0.0001160607,0.00009034055,0.0006617734,0.281948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005228139,"about_ca_system_score_gemma":0.00002898996,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000169962,"about_ca_topic_score_gemma":0.0002637553,"domain_scores_codex":[0.9986952,0.00001255757,0.0003582656,0.0003718576,0.0001999396,0.000362192],"domain_scores_gemma":[0.9986077,0.00001928793,0.00005538551,0.001152078,0.00001602614,0.0001495328],"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":[0.000005004314,0.00001117627,0.000002510733,0.0004504226,0.0001129833,0.0003984229,0.000008636226,0.00005226269,0.00005810217,0.00003709638,0.9986395,0.0002239311],"study_design_scores_gemma":[0.0002691496,0.0000219885,0.00001123271,0.00007098752,0.00009677288,0.00002820481,0.00001602929,0.00006928488,0.00004528696,0.000009067276,0.9989657,0.0003962867],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000009410769,0.000004986007,0.0001726205,0.000004375295,0.001383419,0.0002149068,0.9969621,0.000848733,0.0003994848],"genre_scores_gemma":[0.0001372071,0.0005355853,0.0001586575,0.00009395006,0.0003348321,0.00003207292,0.998596,0.00005812059,0.00005361068],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2711939,"threshold_uncertainty_score":0.9998482,"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."}}