{"id":"W1970623882","doi":"10.1007/s10460-014-9530-6","title":"Characterizing alternative food networks in China","year":2014,"lang":"en","type":"article","venue":"Agriculture and Human Values","topic":"Organic Food and Agriculture","field":"Agricultural and Biological Sciences","cited_by":139,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"China; Typology; Agribusiness; Regional science; Geography; Agriculture; Economy; Economics","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":[0.0005623445,0.0002327998,0.0004245033,0.003292876,0.001084471,0.001205045,0.0006342823,0.0003573161,0.002068674],"category_scores_gemma":[0.001769773,0.0001731544,0.0003799722,0.005762822,0.0009011917,0.001407408,0.0008478501,0.0001804365,0.0001213464],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003920558,"about_ca_system_score_gemma":0.002069214,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08419375,"about_ca_topic_score_gemma":0.1008503,"domain_scores_codex":[0.9996203,0.00008245659,0.00001587477,0.0001063919,0.00006803781,0.0001069229],"domain_scores_gemma":[0.9988293,0.0003824651,0.0003040073,0.0001005845,0.0002185012,0.0001652127],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0003031127,0.00013242,0.776902,0.0001590612,0.0002302942,0.0006699462,0.001786647,0.1182404,0.002317374,0.05711041,0.00206692,0.04008142],"study_design_scores_gemma":[0.00004100697,0.0000870169,0.5438161,0.00002985165,0.0001499832,0.0001527295,0.002745678,0.4136868,0.0007170329,0.03287182,0.005654043,0.00004791477],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966552,0.0001083236,0.001095437,0.00005857457,0.00000152774,0.00001018958,0.0003330577,0.000007845214,0.001729781],"genre_scores_gemma":[0.9989453,0.00005665038,0.0003315719,0.000005089353,0.000001937093,0.000009717625,0.0003063151,0.000001727157,0.0003416504],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08419375,"threshold_uncertainty_score":0.1674074,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009632317360161376,"score_gpt":0.1950727552113387,"score_spread":0.1854404378511773,"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."}}