{"id":"W4398573922","doi":"10.7910/dvn/pkjufn/jh3c9a","title":"FCC2001.249.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":[0.00005838968,0.0003759512,0.0004972176,0.0001597306,0.00004311568,0.00003584959,0.0007103527,0.0005412831,0.01059403],"category_scores_gemma":[0.00002171713,0.000393443,0.0001170775,0.0001852709,0.00005251955,0.0001160722,0.00009026428,0.0006611531,0.2845506],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005201271,"about_ca_system_score_gemma":0.00002833514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001834586,"about_ca_topic_score_gemma":0.0002796059,"domain_scores_codex":[0.9986954,0.00001246428,0.0003583905,0.0003718425,0.0001999476,0.0003619356],"domain_scores_gemma":[0.9986084,0.00001879498,0.00005537902,0.001151919,0.00001602419,0.0001494476],"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":[0.000005017104,0.00001138055,0.000002563291,0.0004477554,0.0001131836,0.0004021878,0.000008576477,0.00005308241,0.00003699653,0.00003618609,0.998639,0.0002440402],"study_design_scores_gemma":[0.0002700594,0.00002261243,0.00001357159,0.0000701589,0.00009700307,0.00002825623,0.00001620034,0.00007035114,0.00003461493,0.00000902234,0.998971,0.0003971888],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000009529214,0.000004927466,0.0001713045,0.000004469976,0.001380828,0.0002131437,0.9969487,0.0008685124,0.000398556],"genre_scores_gemma":[0.0001370659,0.0005238688,0.000158774,0.0000941035,0.0003293383,0.00003174779,0.9986001,0.00005908317,0.00006597632],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2739566,"threshold_uncertainty_score":0.9998518,"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."}}