{"id":"W4398747323","doi":"10.7910/dvn/pkjufn/qm9yyq","title":"FCC2001.324.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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001137396,0.003499602,0.001720582,0.004333948,0.001184722,0.003304258,0.003829828,0.003070594,0.1009791],"category_scores_gemma":[0.005614161,0.0008749311,0.001588425,0.006841457,0.0006277607,0.001898301,0.002275684,0.001969877,0.1904623],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001768722,"about_ca_system_score_gemma":0.002285532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03662113,"about_ca_topic_score_gemma":0.05491493,"domain_scores_codex":[0.9987691,0.0002139758,0.0001156798,0.0003853663,0.000256845,0.0002589735],"domain_scores_gemma":[0.9977538,0.0004323249,0.0001786024,0.0007601372,0.0005881076,0.0002868767],"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":[0.00003766927,0.00001334206,0.0002168871,0.0002217136,0.00001496836,0.00000884164,0.000007816631,0.0001895258,0.00005025461,0.000235922,0.9981703,0.000832679],"study_design_scores_gemma":[0.0003241149,0.00003354974,0.002755808,0.0002875223,0.00003190135,0.00005691517,0.00008277578,0.001021234,0.0004031114,0.001461738,0.993501,0.00004024548],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000821939,0.00004486137,0.00003775553,0.00004829291,0.00003268319,0.000005426805,0.9985514,0.0005049675,0.0006924068],"genre_scores_gemma":[0.0002448701,0.00002853514,0.0001013966,0.00003276235,0.000007819591,0.00002084274,0.9990529,0.00006965166,0.0004411484],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8990209,"threshold_uncertainty_score":0.3378089,"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."}}