{"id":"W4366825715","doi":"10.3390/jrfm16050255","title":"Analysis of Trends in Mortgage Lending in the Agricultural Sector of Ukraine","year":2023,"lang":"en","type":"article","venue":"Journal of risk and financial management","topic":"Agriculture Market Analysis Ukraine","field":"Agricultural and Biological Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Loan; Agriculture; Business; Agrarian society; Product (mathematics); Capital (architecture); Hierarchy; Financial system; Finance; Economics; Market economy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0005315882,0.00007329418,0.0001820884,0.001644079,0.0002029606,0.0004810844,0.0001540941,0.0001190638,0.0005182442],"category_scores_gemma":[0.001441149,0.00007626513,0.0001433186,0.001543356,0.0001613494,0.0003569359,0.0003085427,0.0001812061,0.0001355226],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005293064,"about_ca_system_score_gemma":0.0006408896,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01295717,"about_ca_topic_score_gemma":0.01234685,"domain_scores_codex":[0.9997604,0.00004878124,0.00003887904,0.00005126975,0.00006162599,0.00003908723],"domain_scores_gemma":[0.9986132,0.0002343714,0.0006057891,0.00006201972,0.0003936768,0.00009089111],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004321642,0.00002134566,0.9799849,0.00004259863,0.0000256706,0.0002302269,0.001852859,0.0005147829,0.001174286,0.0004684372,0.0003577978,0.01528397],"study_design_scores_gemma":[5.37226e-7,0.0000149758,0.9970355,0.00000724409,0.000005149425,0.00009857729,0.0007704069,0.0007697797,0.00023343,0.00005195208,0.00101017,0.000002275289],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9987475,0.0001241227,0.0001425249,0.00003929189,0.000001260255,0.00000385158,0.0003426944,0.000009291747,0.0005894534],"genre_scores_gemma":[0.9985974,0.0001617269,0.0002590011,0.000007529562,0.000003039469,0.000005232469,0.0004975181,0.000003051793,0.0004654414],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01295717,"threshold_uncertainty_score":0.02576345,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01071273447232403,"score_gpt":0.2145202022573071,"score_spread":0.203807467784983,"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."}}