{"id":"W4286388476","doi":"10.21272/mer.2021.94.09","title":"Scientific Aspects of the Formation of the Logistics System of Agricultural Companies","year":2021,"lang":"en","type":"article","venue":"Mechanism of an economic regulation","topic":"Agriculture Market Analysis Ukraine","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Business; Agriculture; Industrial organization; Agricultural productivity; China; Productivity; Work (physics); Product (mathematics); Economics; Economic growth","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":[],"consensus_categories":[],"category_scores_codex":[0.0003416455,0.00008139907,0.0002397957,0.00001141761,0.000107947,0.00001990285,0.0002885236,0.00005940346,0.0000417249],"category_scores_gemma":[0.00003773381,0.00002444665,0.0001730874,0.0002905135,0.000114983,0.0001595535,0.00008887773,0.00003409953,8.283498e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005141339,"about_ca_system_score_gemma":0.00001700434,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006127597,"about_ca_topic_score_gemma":0.0008633295,"domain_scores_codex":[0.9989592,0.0001496363,0.0004923611,0.0001400984,0.0001771708,0.00008153716],"domain_scores_gemma":[0.9986583,0.00006302464,0.0008565939,0.0001432584,0.0002613429,0.00001745572],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000007183908,0.00003975371,0.0002278384,0.00005795605,0.00002080619,3.460251e-8,0.0002342134,0.003084904,0.902542,0.09309688,0.00004207896,0.000646367],"study_design_scores_gemma":[0.00008278197,0.00004561912,0.274219,0.00006455723,0.00005494714,0.000005637335,0.00204207,0.00725571,0.7127723,0.00337166,0.00002615506,0.00005957552],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982914,0.00002011853,0.00007596968,0.0001934031,0.0002247535,0.0001617126,0.00005173405,0.000006834995,0.0009740714],"genre_scores_gemma":[0.9996656,0.000001493265,0.00008537015,0.000002813236,0.00004393217,0.000001552448,0.00007093702,5.184976e-7,0.0001278319],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2739911,"threshold_uncertainty_score":0.09969054,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01255448892051799,"score_gpt":0.1798093562477959,"score_spread":0.1672548673272779,"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."}}