{"id":"W6968168780","doi":"10.5281/zenodo.13370486","title":"Open Trade Statistics Database","year":2024,"lang":"en","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Raw data; Code (set theory); Commodity; SQL; Latin Americans; Open data","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":[],"consensus_categories":[],"category_scores_codex":[0.007320026,0.001227829,0.001773817,0.02016082,0.001663532,0.009599886,0.003380469,0.001955722,0.1735862],"category_scores_gemma":[0.03358223,0.0007038302,0.001309389,0.03024718,0.0006790031,0.00562976,0.003844926,0.002876518,0.1574308],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002745227,"about_ca_system_score_gemma":0.009148159,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008984673,"about_ca_topic_score_gemma":0.005742161,"domain_scores_codex":[0.989504,0.001571548,0.002738466,0.001735176,0.003701791,0.0007489906],"domain_scores_gemma":[0.9704841,0.007959052,0.003144536,0.005154043,0.01184492,0.001413347],"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":[0.0001851665,0.00006544586,0.003498794,0.0008180093,0.00007076014,0.0001332371,0.0002011059,0.0007358582,0.0002054693,0.01656403,0.9206088,0.05691348],"study_design_scores_gemma":[0.00002984896,0.000009539309,0.00182725,0.0002114654,0.00001641088,0.00008028811,0.0001105353,0.000427511,0.0001462044,0.004879822,0.9922357,0.00002541171],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001844995,0.0009391249,0.008777729,0.001251283,0.0005877062,0.0003363801,0.920682,0.006005424,0.0595753],"genre_scores_gemma":[0.006837833,0.001012817,0.01151852,0.0007183802,0.000331606,0.0008752309,0.9578815,0.002245642,0.0185784],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1735862,"threshold_uncertainty_score":0.5807038,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06703813525417833,"score_gpt":0.3125450633612954,"score_spread":0.2455069281071171,"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."}}