{"id":"W2591423181","doi":"10.3390/su9020313","title":"Analyzing Agricultural Agglomeration in China","year":2017,"lang":"en","type":"article","venue":"Sustainability","topic":"Regional Economics and Spatial Analysis","field":"Economics, Econometrics and Finance","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"U.S. Department of Agriculture","keywords":"China; Economic geography; Agriculture; Gini coefficient; Geography; Economies of agglomeration; Diversification (marketing strategy); Spatial analysis; Sustainable development; Agricultural productivity; Agricultural economics; Economics; Ecology; Business; Economic growth; Inequality; Biology","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":[0.0006651779,0.0002499993,0.0003876348,0.003550245,0.0007870308,0.0007254183,0.0003434604,0.0002174988,0.001570764],"category_scores_gemma":[0.00183659,0.000142722,0.0005412081,0.004441699,0.0007460194,0.0005016878,0.001231372,0.0001665875,0.0001220237],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003032198,"about_ca_system_score_gemma":0.001520068,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1072542,"about_ca_topic_score_gemma":0.08650083,"domain_scores_codex":[0.9995992,0.00007975109,0.0000158171,0.00007222631,0.00008457983,0.0001484364],"domain_scores_gemma":[0.9991467,0.0002062169,0.0002388014,0.00008111477,0.0002106533,0.0001164888],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001307106,0.00003750524,0.8897059,0.00005544623,0.0001673699,0.0004818939,0.001817754,0.0610375,0.0008309392,0.02005923,0.001327169,0.02434856],"study_design_scores_gemma":[0.00001892079,0.00004547587,0.8936402,0.0000161119,0.00006121345,0.00007411815,0.002088761,0.09221521,0.0003454289,0.007293135,0.004182755,0.0000185717],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962893,0.00009195592,0.001149446,0.00006537176,0.000001251128,0.00001443133,0.0001722067,0.00001391508,0.002202175],"genre_scores_gemma":[0.9989265,0.00005842655,0.0004156984,0.000005721629,0.000001682374,0.00001013592,0.0002410225,0.000002360271,0.0003384248],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1072542,"threshold_uncertainty_score":0.2132599,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01440878139473177,"score_gpt":0.2344622098245712,"score_spread":0.2200534284298394,"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."}}