{"id":"W4328025129","doi":"10.5267/j.uscm.2023.2.011","title":"Risk management in the adoption of smart farming technologies by rural farmers","year":2023,"lang":"en","type":"article","venue":"Uncertain Supply Chain Management","topic":"Agricultural Development and Management","field":"Agricultural and Biological Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Erasmus+; Khon Kaen University; European Commission","keywords":"Agriculture; Business; Environmental economics; Government (linguistics); Sustainability; Production (economics); Product (mathematics); Structural equation modeling; Marketing; Confirmatory factor analysis; Agricultural science; Computer science; Economics","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":[0.002970292,0.0002578186,0.0001337418,0.0005275626,0.0007714233,0.001843369,0.0003302878,0.0007635608,0.001456866],"category_scores_gemma":[0.008693376,0.0002117872,0.0003167252,0.0004797832,0.0008863246,0.001970621,0.00121726,0.0007539386,0.0001200993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007617907,"about_ca_system_score_gemma":0.001249306,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001157909,"about_ca_topic_score_gemma":0.001651406,"domain_scores_codex":[0.9978305,0.001185444,0.0001302211,0.0001859808,0.0004363078,0.0002315668],"domain_scores_gemma":[0.9934361,0.003285932,0.002151283,0.0002460372,0.000543915,0.000336651],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001868131,0.001096246,0.7065282,0.0004349143,0.0001228453,0.002018442,0.09124346,0.003529031,0.007342863,0.01002763,0.0007541166,0.1767153],"study_design_scores_gemma":[0.00007214195,0.002146586,0.6974298,0.0007390513,0.0002826859,0.002217631,0.2163139,0.02495617,0.005683925,0.02347906,0.02648345,0.0001956527],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9933929,0.0001234577,0.002138459,0.0005309923,0.00000402512,0.00004021217,0.00000960579,0.00000785476,0.003752589],"genre_scores_gemma":[0.9987034,0.0001035852,0.0008147812,0.00003450577,0.000002012341,0.00001270787,0.000004390666,9.336685e-7,0.000323753],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002970292,"threshold_uncertainty_score":0.01570863,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01159384846014155,"score_gpt":0.2092873001459301,"score_spread":0.1976934516857885,"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."}}