{"id":"W4316371207","doi":"10.1111/rsp3.12633","title":"The impact of COVID‐19 on agricultural market integration in Eastern Canada","year":2023,"lang":"en","type":"article","venue":"Regional Science Policy & Practice","topic":"COVID-19 Pandemic Impacts","field":"Economics, Econometrics and Finance","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Prince Edward Island","funders":"","keywords":"Agriculture; Commodity; Cointegration; Market integration; Pandemic; Order (exchange); Economics; Government (linguistics); Agricultural economics; Business; Coronavirus disease 2019 (COVID-19); International economics; Geography; Market economy; Macroeconomics; Finance","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.002646697,0.0001114306,0.000157446,0.0003658205,0.0002476896,0.0001003355,0.0004789037,0.00003794454,0.00002708983],"category_scores_gemma":[0.01871349,0.00007693616,0.00006118193,0.002548128,0.0002308223,0.0006873482,0.00007577631,0.0001814052,0.00007481101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002514895,"about_ca_system_score_gemma":0.003259748,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8330361,"about_ca_topic_score_gemma":0.1304801,"domain_scores_codex":[0.9986477,0.0000561772,0.0003666247,0.0002912131,0.0002053555,0.0004328655],"domain_scores_gemma":[0.9973573,0.001649235,0.0004470037,0.000260405,0.00007281875,0.0002132417],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.000650362,0.000226202,0.1297255,0.00003341615,0.0000729403,0.00004135305,0.006627724,0.01771433,0.0008799601,0.6322696,0.2043637,0.007394877],"study_design_scores_gemma":[0.0003809936,0.0001133959,0.8959925,0.00002400218,0.000002335798,0.000039437,0.001431237,0.01009588,0.00002631,0.009389509,0.08229546,0.0002089856],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8363237,0.00013434,0.00004430183,0.1207439,0.0002128886,0.0002938405,0.000070329,0.00002690485,0.04214974],"genre_scores_gemma":[0.9963445,0.0001960812,0.00001599148,0.002081816,0.00009399452,0.000009820659,0.000004137515,0.000005371623,0.001248251],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7662669,"threshold_uncertainty_score":0.9895523,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08266876214337797,"score_gpt":0.3628315714457965,"score_spread":0.2801628093024185,"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."}}