{"id":"W3081227551","doi":"10.5539/ibr.v13n9p101","title":"Between Tradition and Sustainable Innovation: Empirical Evidence for the Role of Geographical Indications","year":2020,"lang":"en","type":"article","venue":"International Business Research","topic":"Rural development and sustainability","field":"Agricultural and Biological Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sustainability; Selection (genetic algorithm); Product (mathematics); Triple bottom line; Business; Marketing; Empirical research; Empirical evidence; Content analysis; Industrial organization; Regional science; Sociology; Computer science; Social science; Ecology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01721365,0.0003737017,0.0007292979,0.004264459,0.001325985,0.005793483,0.001822807,0.001960618,0.01648951],"category_scores_gemma":[0.0893366,0.0004057277,0.0008480452,0.0063428,0.009706382,0.007288184,0.006249954,0.001795222,0.000641226],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002620191,"about_ca_system_score_gemma":0.003123991,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004480878,"about_ca_topic_score_gemma":0.004447041,"domain_scores_codex":[0.9870734,0.006231972,0.000754633,0.002266986,0.002928887,0.0007441375],"domain_scores_gemma":[0.5845469,0.3650212,0.0325501,0.007707733,0.007425048,0.002748971],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008168701,0.0005055657,0.6114602,0.004838365,0.0008912602,0.001825802,0.05105844,0.00179866,0.0008447864,0.1283347,0.001299781,0.1963255],"study_design_scores_gemma":[0.0001578957,0.0007265883,0.7647866,0.007470634,0.001352314,0.001969889,0.08076003,0.004362362,0.001209635,0.09647343,0.04054147,0.0001890417],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8405365,0.02410802,0.00887184,0.005641531,0.0001181757,0.00008802967,0.0002313245,0.00002926337,0.1203754],"genre_scores_gemma":[0.9951583,0.003155349,0.000826648,0.0001423854,0.00003655086,0.0000192423,0.00003583488,0.0000124054,0.0006133713],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01721365,"threshold_uncertainty_score":0.09103554,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2091623872402039,"score_gpt":0.3947612090343522,"score_spread":0.1855988217941483,"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."}}