{"id":"W6957615118","doi":"10.6068/dp14ba88929f626","title":"Trend 1992 - 2000. Statistics Canada. CANSIM: International Trade - Merchandise Imports | Country: Canada | Table: Merchandise imports and exports balance of payments and customs-based price and volume indexes for all countries | Variable: Customs, Fresh fruits and berries, imports, Volume index, Laspeyres fixed weighted | Units: 1992=100, 1992-2000. Data-Planet™ Statistical Ready Reference by Conquest Systems, Inc. Dataset-ID: 075-001-131.","year":2015,"lang":"en","type":"other","venue":"Data Planet","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Balance of payments; Economic statistics; Official statistics; Census; Price index; Balance of trade; Balance (ability); International comparisons; Payment; Summary statistics","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":[0.001786906,0.002371351,0.002246246,0.008855341,0.002907231,0.004747923,0.004340774,0.001276834,0.1011617],"category_scores_gemma":[0.01434707,0.001573424,0.001715269,0.04183945,0.0005803505,0.002434273,0.002018707,0.002737693,0.06632528],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04265793,"about_ca_system_score_gemma":0.1076953,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.992337,"about_ca_topic_score_gemma":0.9898811,"domain_scores_codex":[0.9965054,0.0001999173,0.000356805,0.0004848085,0.001625492,0.0008276416],"domain_scores_gemma":[0.9736778,0.0008545656,0.0008483634,0.0007731383,0.02267848,0.001167604],"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":[0.00001996763,0.000005165054,0.0008261438,0.0002065764,0.00001568762,0.000006783827,0.00001725536,0.00008746989,0.00000876635,0.0003566,0.9968431,0.001606511],"study_design_scores_gemma":[0.0001046969,0.00000899987,0.01863901,0.0006769675,0.00004912097,0.00002426311,0.0003575227,0.0003622734,0.0001529786,0.0005595,0.9790016,0.00006297736],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.00005165866,0.00004496854,0.0000200926,0.00008908129,0.00002274875,0.00001085609,0.9986695,0.00005375874,0.001037253],"genre_scores_gemma":[0.00062721,0.0002318299,0.0002944062,0.0001132643,0.00001272038,0.00008308242,0.9940727,0.00009805517,0.004466749],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1011617,"threshold_uncertainty_score":0.3384197,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01639541267468955,"score_gpt":0.2425351664057337,"score_spread":0.2261397537310441,"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."}}