{"id":"W4416418979","doi":"10.1016/j.ijpe.2025.109861","title":"Platform-led or firm-led? An analysis of artificial intelligence development strategies in agricultural supply chains","year":2025,"lang":"en","type":"article","venue":"International Journal of Production Economics","topic":"Supply Chain and Inventory Management","field":"Business, Management and Accounting","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University","funders":"Natural Science Foundation of Zhejiang Province; National Social Science Fund of China; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; Zhejiang Gongshang University","keywords":"Agriculture; Yield (engineering); Supply chain; Applications of artificial intelligence; Agricultural development; Development (topology)","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002038672,0.0005190463,0.000491233,0.001355256,0.000924169,0.003122415,0.0009992023,0.001551708,0.008988916],"category_scores_gemma":[0.006432767,0.0004489661,0.0007980471,0.0009563499,0.001553214,0.003399637,0.001657196,0.0009809635,0.0005004181],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002903468,"about_ca_system_score_gemma":0.001938164,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0100099,"about_ca_topic_score_gemma":0.008141299,"domain_scores_codex":[0.9985429,0.0006020197,0.00004751056,0.0001982804,0.0001663206,0.0004430261],"domain_scores_gemma":[0.994358,0.003137554,0.001218075,0.0001603126,0.0004404249,0.0006856098],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.0006579817,0.0007987139,0.1100357,0.0004127916,0.0003686187,0.002812296,0.003276536,0.5483488,0.006938233,0.2684353,0.001884792,0.05603016],"study_design_scores_gemma":[0.0001123994,0.0006499744,0.02980307,0.0001355318,0.0001384646,0.0003292729,0.007606472,0.8635241,0.001175464,0.0918235,0.004592001,0.0001097701],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9387406,0.0004917864,0.03489301,0.0009260476,0.00001228215,0.0002217249,0.0001431479,0.00003494754,0.02453655],"genre_scores_gemma":[0.9958615,0.0001883212,0.001674729,0.0000341647,0.000004284688,0.00004615356,0.00003110675,0.000004685774,0.002155167],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0100099,"threshold_uncertainty_score":0.0300709,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03422767782914313,"score_gpt":0.2752720945689822,"score_spread":0.2410444167398391,"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."}}