{"id":"W2728274632","doi":"10.1111/jwip.12078","title":"Climate change and<i>terroir</i>: The challenge of adapting geographical indications","year":2017,"lang":"en","type":"article","venue":"The Journal of World Intellectual Property","topic":"Organic Food and Agriculture","field":"Agricultural and Biological Sciences","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Terroir; Optimal distinctiveness theory; Product (mathematics); Climate change; Geography; Quality (philosophy); Geographical indication; Environmental resource management; Ecology; Regional science; Psychology; Economics; Biology; Mathematics; Food science; Social psychology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008492256,0.0001060558,0.0001798731,0.00001510146,0.0008667909,0.00007071233,0.0007859787,0.00004093034,0.0002470553],"category_scores_gemma":[0.0003196697,0.00001804552,0.0000978962,0.0001579714,0.0003080605,0.0001622225,0.0002304033,0.0003826246,0.000005933678],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005252343,"about_ca_system_score_gemma":0.000005030375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009764256,"about_ca_topic_score_gemma":0.000702167,"domain_scores_codex":[0.9990892,0.0001375278,0.0002995649,0.00008507738,0.0002094487,0.0001792119],"domain_scores_gemma":[0.9988645,0.0003812545,0.0004735369,0.0001078577,0.0001150583,0.00005782591],"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":[0.0006560844,0.0006108645,0.003489566,0.00005150674,0.000239331,0.000007428104,0.02133391,0.000001349294,0.1530556,0.001775452,0.01903848,0.7997404],"study_design_scores_gemma":[0.001325344,0.007155103,0.5904415,0.001730146,0.0006470553,0.0007718643,0.0152187,0.0004420882,0.02632405,0.003931439,0.3509082,0.001104506],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8502457,0.002304842,0.000001415692,0.1437751,0.0001667843,0.0002618409,0.00001164689,0.00001193184,0.003220653],"genre_scores_gemma":[0.9966474,0.002385367,0.00001093977,0.0002399275,0.0005513728,0.00000225742,5.27811e-7,0.000001025622,0.0001612273],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7986359,"threshold_uncertainty_score":0.6666742,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06783664415558427,"score_gpt":0.2386713615639989,"score_spread":0.1708347174084147,"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."}}