{"id":"W2270712509","doi":"","title":"Food Clusters, Rural Development and Creative Economy","year":2015,"lang":"en","type":"article","venue":"Journal of rural and community development","topic":"Entrepreneurship Studies and Influences","field":"Business, Management and Accounting","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Nexus (standard); Creative economy; Conceptual framework; Food processing; Cluster (spacecraft); Process (computing); Business; Consumption (sociology); Conceptual model; Economic geography; Economic growth; Marketing; Regional science; Creativity; Economics; Political science; Computer science; Geography; Sociology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006936008,0.0001594502,0.0002601644,0.0001266568,0.0005412677,0.0002088641,0.0001987363,0.00003379694,0.00001508392],"category_scores_gemma":[0.0000604048,0.0001166805,0.00002906953,0.00009408357,0.0000811334,0.0008173752,0.0004316523,0.000300444,0.000008577971],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005659184,"about_ca_system_score_gemma":0.00006483452,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001370135,"about_ca_topic_score_gemma":0.0001726781,"domain_scores_codex":[0.999149,0.0000428754,0.0004200213,0.00004725956,0.0001616468,0.0001791673],"domain_scores_gemma":[0.9992042,0.00005419962,0.0003432558,0.00007861662,0.0002701822,0.0000495182],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0006007464,0.0005242591,0.4387985,0.000412902,0.0009104502,0.0000188211,0.05807128,0.00004259366,0.00002883585,0.002971441,0.009363239,0.488257],"study_design_scores_gemma":[0.00261828,0.0003514864,0.376369,0.0005728722,0.00007709939,0.00009320247,0.2398536,0.00002376223,0.0003103059,0.003961544,0.3751597,0.0006091378],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9917961,0.0009593759,0.00002527941,0.0009473827,0.0001401718,0.00007300705,2.788052e-7,0.00001166866,0.006046725],"genre_scores_gemma":[0.9979053,0.00007652542,0.0008491567,0.0009216302,0.0001365159,0.000003725671,0.000003933373,0.000006574986,0.00009666552],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4876478,"threshold_uncertainty_score":0.4758093,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03964980817775262,"score_gpt":0.2335579392544894,"score_spread":0.1939081310767368,"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."}}