{"id":"W4398442016","doi":"10.7910/dvn/pkjufn/z1yiql","title":"FCC2001.130.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":[0.00005817562,0.0003760316,0.0004975713,0.0001595808,0.00004286153,0.00003575365,0.0007096864,0.0005416286,0.01119329],"category_scores_gemma":[0.0000217067,0.0003969208,0.0001171104,0.0001850729,0.00005226261,0.0001155669,0.00009029798,0.0006618904,0.2866639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005217895,"about_ca_system_score_gemma":0.00002898161,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001699826,"about_ca_topic_score_gemma":0.0002677544,"domain_scores_codex":[0.9986947,0.00001257216,0.000358558,0.0003719956,0.0002000054,0.0003622064],"domain_scores_gemma":[0.9986078,0.00001923847,0.00005538596,0.001152038,0.00001598144,0.0001495197],"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":[0.000005022007,0.00001137499,0.000002378031,0.0004479956,0.0001135993,0.0005162171,0.000007469582,0.00005274257,0.00003759311,0.00003696468,0.9985356,0.0002330123],"study_design_scores_gemma":[0.0002697295,0.00002261055,0.00001337429,0.00006966782,0.00009709715,0.00002821038,0.0000168062,0.00007054115,0.00003542312,0.000009123263,0.9989712,0.0003962714],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00000988804,0.000005025803,0.0001746075,0.000004367401,0.001377343,0.0002127032,0.9969495,0.0008488286,0.0004177513],"genre_scores_gemma":[0.0001457961,0.0005276239,0.0001606727,0.00009407558,0.0003340639,0.00003171276,0.9985837,0.00005812199,0.00006422326],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2754707,"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."}}