{"id":"W2993451959","doi":"10.1111/meca.12279","title":"Aid to agriculture, trade and structural change","year":2019,"lang":"en","type":"article","venue":"Metroeconomica","topic":"International Development and Aid","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Landlocked country; Openness to experience; Agriculture; Economics; Industrialisation; Developing country; Panel data; International economics; Structural adjustment; International trade; Economic growth; Econometrics; Market economy; Political science","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0006968961,0.0001343358,0.0001920465,0.001027709,0.0003162695,0.001366568,0.0001585434,0.0003860032,0.009715466],"category_scores_gemma":[0.00469973,0.00004951237,0.0002074307,0.001596702,0.001373773,0.0005457872,0.000673982,0.0005796543,0.0003549249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008318056,"about_ca_system_score_gemma":0.000615142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003410125,"about_ca_topic_score_gemma":0.004300934,"domain_scores_codex":[0.9996285,0.000142283,0.00001414711,0.00003717434,0.00006060503,0.0001171614],"domain_scores_gemma":[0.9932239,0.003622853,0.002101402,0.0002082241,0.0003456482,0.0004979796],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005209675,0.0006355968,0.6817172,0.0004354241,0.0003745466,0.0008741328,0.000945556,0.07987024,0.002048437,0.1416716,0.006141374,0.08476498],"study_design_scores_gemma":[0.00008429207,0.0004748423,0.8489465,0.0002055259,0.0001943914,0.0005449423,0.002208638,0.01845454,0.001380761,0.08924227,0.03823608,0.00002732302],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9492815,0.00354452,0.001160927,0.003616136,0.00005685585,0.00001767931,0.0003996606,0.00003888667,0.04188381],"genre_scores_gemma":[0.9979031,0.0007416637,0.0000582342,0.00006685415,0.00003431587,0.000001532861,0.00003933778,0.000001853634,0.001153172],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009715466,"threshold_uncertainty_score":0.03250146,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01927909672784575,"score_gpt":0.2687551768191941,"score_spread":0.2494760800913484,"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."}}