{"id":"W6945474892","doi":"10.25318/1210005601-eng","title":"Merchandise import and export price and volume indexes by sector and sub-sector, customs and balance of payments basis, for all countries, monthly (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":"Index (typography); Balance of payments; Fishing; Payment; Price index; Weighting; Agriculture; Table (database)","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":[0.0006651144,0.001324574,0.00114556,0.006353926,0.0007924451,0.002026088,0.001635625,0.0006924761,0.05638389],"category_scores_gemma":[0.006275469,0.0006602876,0.0008014028,0.02320124,0.0003244359,0.001043499,0.0008172838,0.001536617,0.05342431],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.006599481,"about_ca_system_score_gemma":0.01149565,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.6983835,"about_ca_topic_score_gemma":0.7081488,"domain_scores_codex":[0.9987302,0.00006696511,0.0001680266,0.0002300257,0.0005608427,0.0002439267],"domain_scores_gemma":[0.9943715,0.0004887356,0.0006119449,0.0003377778,0.003917721,0.0002723989],"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":[0.00002764504,0.0000106605,0.002235898,0.0002328928,0.00001579236,0.00001061815,0.00001554507,0.0001877295,0.00002493825,0.0004530045,0.9951499,0.00163555],"study_design_scores_gemma":[0.0001252476,0.00001216583,0.03963355,0.0003435239,0.000033346,0.00003864458,0.0001914098,0.0004655835,0.0002528774,0.0003704636,0.958499,0.00003417098],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001585623,0.00003053937,0.00001761466,0.00002984844,0.000009279911,0.000006000464,0.9988565,0.00003421321,0.0008573229],"genre_scores_gemma":[0.0006840563,0.00009627306,0.0001099515,0.00002034391,0.000006433908,0.00003375019,0.9969677,0.00002297839,0.002058488],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.6983835,"threshold_uncertainty_score":0.6067855,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007901283474690188,"score_gpt":0.2490527788200131,"score_spread":0.2411514953453229,"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."}}