{"id":"W3168479381","doi":"","title":"Probability to buy agricultural products from different sales points during COVID-19: An exemplary scenario analysis","year":2021,"lang":"en","type":"article","venue":"Fresenius environmental bulletin","topic":"COVID-19 Pandemic Impacts","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Agriculture; Product (mathematics); Quarter (Canadian coin); Marketing; Business; Population; Pandemic; Order (exchange); Agricultural economics; Coronavirus disease 2019 (COVID-19); Economics; Geography; Finance","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":[0.001269674,0.0004212389,0.0003395788,0.001573033,0.0003650688,0.0009820492,0.0006478359,0.0008314736,0.009260538],"category_scores_gemma":[0.002418305,0.0001372002,0.001149922,0.001140116,0.0003357265,0.0007247523,0.0006975962,0.0009591157,0.0008319324],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007617609,"about_ca_system_score_gemma":0.0003446607,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01050554,"about_ca_topic_score_gemma":0.007811826,"domain_scores_codex":[0.9992582,0.0003108807,0.00005339184,0.0001405668,0.00007770542,0.0001592561],"domain_scores_gemma":[0.9966637,0.0023809,0.0003936086,0.0001032454,0.0002273449,0.000231141],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001552723,0.0008038743,0.9203936,0.000255817,0.0004681413,0.002551605,0.001042756,0.047292,0.0008718927,0.004545358,0.005068758,0.01515357],"study_design_scores_gemma":[0.00005647524,0.001929273,0.6607873,0.0001011126,0.0004066223,0.003437403,0.01126028,0.3123839,0.001443713,0.003961312,0.004079712,0.0001528572],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9914138,0.0001355954,0.001501376,0.0001787561,0.00001317554,0.0000625674,0.004290335,0.00002657505,0.002377946],"genre_scores_gemma":[0.9956871,0.00009298788,0.0006714726,0.00001352232,0.000005986195,0.00004544029,0.002578448,0.00000349177,0.0009016143],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01050554,"threshold_uncertainty_score":0.03097957,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03646960850095219,"score_gpt":0.2271303939465876,"score_spread":0.1906607854456354,"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."}}