{"id":"W2958468082","doi":"10.18170/dvn/5acox1","title":"\"One Belt And One Road\" shipping data","year":2018,"lang":"en","type":"dataset","venue":"","topic":"Maritime Ports and Logistics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Macro; Quarter (Canadian coin); Transport engineering; Road traffic; Geography; Engineering; Computer science; Archaeology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001685029,0.0001914226,0.0002804045,0.00006466038,0.00004317796,0.00009065014,0.0004352759,0.0002278242,0.002777162],"category_scores_gemma":[0.00006504314,0.0002022126,0.00001278592,0.00004727803,0.00006136213,0.00007693789,0.0004872181,0.0002595871,0.00008851401],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001344475,"about_ca_system_score_gemma":0.00001797607,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009539928,"about_ca_topic_score_gemma":0.001113573,"domain_scores_codex":[0.9991034,0.000007423678,0.000225595,0.0002914441,0.0001460473,0.0002261318],"domain_scores_gemma":[0.9986466,0.00003084532,0.00003031831,0.001179957,0.00002022362,0.00009207863],"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":[7.772878e-7,0.00001342166,0.000001533511,0.0003313491,0.00006786443,0.000007244052,0.000001905229,0.000004419929,0.000001335726,0.00002725509,0.9960975,0.003445377],"study_design_scores_gemma":[0.00007046921,0.00001344249,0.00009529293,0.00007939681,0.00009796923,0.000004420689,0.000001911571,0.002180329,0.000002698125,0.00007009871,0.9971088,0.0002752364],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000002573297,0.0004928224,0.0009090609,0.0000309824,0.0003581711,0.00009515732,0.9936996,0.0001232396,0.004288395],"genre_scores_gemma":[0.00003332932,0.001320945,0.002277614,0.00008804625,0.0007323974,0.000003081559,0.9951685,0.000024857,0.0003512128],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.003937182,"threshold_uncertainty_score":0.9981344,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06918980284006139,"score_gpt":0.2558883214629577,"score_spread":0.1866985186228963,"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."}}