{"id":"W6945610462","doi":"10.25318/1210004801-eng","title":"Merchandise imports and exports balance of payments and customs-based price and volume indexes for all countries, quarterly (1997)","year":2019,"lang":"en","type":"dataset","venue":"Statistics Canada Dissemination","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Commodity; Index (typography); Balance of payments; Table (database); Weighting; Payment","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006925793,0.001435739,0.001238136,0.007333111,0.0007299366,0.002174196,0.001643008,0.0006712427,0.05015797],"category_scores_gemma":[0.005989702,0.0007588736,0.0008210451,0.02435563,0.0003195684,0.001079994,0.00082287,0.0015769,0.0597964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005262244,"about_ca_system_score_gemma":0.01004822,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5689704,"about_ca_topic_score_gemma":0.5357285,"domain_scores_codex":[0.9985718,0.00007309232,0.0001850041,0.0002679331,0.0006464499,0.0002556667],"domain_scores_gemma":[0.9946675,0.0004468335,0.0006632611,0.0003515207,0.003611378,0.0002594989],"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":[0.00002493914,0.00001069796,0.002061492,0.0002137611,0.0000157694,0.00001088576,0.00001514977,0.0002043702,0.00002426844,0.000448293,0.9951781,0.00179219],"study_design_scores_gemma":[0.00009703983,0.00001127688,0.03471722,0.0002883499,0.00003189431,0.00004127163,0.0001570053,0.0003715985,0.0002432762,0.0003691465,0.9636415,0.0000304103],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001644194,0.00003228,0.00001866603,0.00002649946,0.00001076537,0.000004870829,0.9989611,0.00003898866,0.0007423757],"genre_scores_gemma":[0.0005236511,0.00009798388,0.00009746608,0.00001470048,0.000006382312,0.00002481994,0.9975898,0.00002478389,0.001620285],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4310296,"threshold_uncertainty_score":0.8671359,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006970465975475675,"score_gpt":0.262315162301097,"score_spread":0.2553446963256213,"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."}}