{"id":"W1536639413","doi":"10.52825/gjae.v57i8.1725","title":"How to deal with the challenges of linking a large number of individual national models: the case of the AGMEMOD Partnership","year":2008,"lang":"en","type":"article","venue":"German Journal of Agricultural Economics","topic":"Agricultural Economics and Policy","field":"Agricultural and Biological Sciences","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Université Catholique de Louvain; Queen's University; Universidade Nova de Lisboa; National and Kapodistrian University of Athens; Institut National de la Recherche Agronomique; Teagasc","keywords":"General partnership; Consistency (knowledge bases); Key (lock); Accession; Computer science; State (computer science); Member states; Process management; Management science; Business; European union; Economics; International trade; Computer security","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005467038,0.0001767996,0.0003467707,0.00001275331,0.0002670723,0.00004324237,0.0007412554,0.00008375602,0.00001457767],"category_scores_gemma":[0.00001406594,0.00003942821,0.0002812761,0.0001784391,0.0001650242,0.0002971941,0.000146578,0.0002376713,0.000001069134],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004215839,"about_ca_system_score_gemma":0.00004753207,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005402149,"about_ca_topic_score_gemma":0.001153735,"domain_scores_codex":[0.9988292,0.000107056,0.0005146667,0.000135646,0.0001752421,0.0002381967],"domain_scores_gemma":[0.9980591,0.000283779,0.001109295,0.00007051365,0.0003879804,0.00008935983],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.001282054,0.001870241,0.02260914,0.0003476565,0.004227214,0.0001425682,0.115831,0.05362606,0.02063555,0.6702383,0.03235781,0.07683234],"study_design_scores_gemma":[0.001659333,0.001223334,0.9100075,0.0002436356,0.0003105928,0.01724141,0.03862454,0.000273305,0.007329113,0.008108199,0.01408566,0.0008933957],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9821565,0.0002105656,9.106588e-7,0.01659451,0.00004552983,0.0001824925,0.0001022572,0.000002791209,0.0007044027],"genre_scores_gemma":[0.9988887,0.0002073702,0.00009188624,0.0002440297,0.0004714215,0.000004044386,0.00000574611,0.000001541774,0.00008526481],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8873984,"threshold_uncertainty_score":0.2054131,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05752745893698144,"score_gpt":0.2428027225169989,"score_spread":0.1852752635800175,"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."}}