{"id":"W4398584572","doi":"10.7910/dvn/pkjufn/oa4hgy","title":"FCC2001.127.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":[0.0000585399,0.0003759771,0.0004975417,0.0001597325,0.00004287105,0.000035843,0.0007100575,0.0005415325,0.01098346],"category_scores_gemma":[0.00002183189,0.0003968755,0.0001171093,0.0001851545,0.00005218306,0.0001161105,0.00009028991,0.0006617033,0.286579],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005238191,"about_ca_system_score_gemma":0.00002904433,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001698474,"about_ca_topic_score_gemma":0.0002606913,"domain_scores_codex":[0.9986949,0.0000125853,0.0003586056,0.000371729,0.0001999707,0.0003621908],"domain_scores_gemma":[0.998609,0.00001928819,0.00005541256,0.001150712,0.00001602513,0.0001495388],"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":[0.000005031772,0.00001138551,0.000002527219,0.000449239,0.0001129829,0.0004075123,0.000008801015,0.00005248645,0.00003962587,0.00003711932,0.998638,0.0002352823],"study_design_scores_gemma":[0.0002703139,0.0000223821,0.00001346814,0.00006971601,0.00009683966,0.00002841218,0.00001617852,0.00006891236,0.00003677473,0.000009144454,0.9989716,0.0003962042],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000009657439,0.000005001045,0.0001726615,0.000004470947,0.001383125,0.0002132337,0.9969455,0.0008487753,0.0004175937],"genre_scores_gemma":[0.0001424347,0.0005279174,0.0001595348,0.00009364959,0.0003345367,0.00003180644,0.9985856,0.00005806744,0.00006641517],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2755955,"threshold_uncertainty_score":0.9998483,"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."}}