{"id":"W3086939863","doi":"10.1038/s41598-020-71918-7","title":"Population genetic analysis in old Montenegrin vineyards reveals ancient ways currently active to generate diversity in Vitis vinifera","year":2020,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Horticultural and Viticultural Research","field":"Agricultural and Biological Sciences","cited_by":65,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Domestication; Viticulture; Genetic diversity; Cultivar; Biology; Diversification (marketing strategy); Montenegro; Adaptability; Diversity (politics); Population; Geography; Botany; Ecology; Regional science; Wine; Demography; Political science","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":[0.0006545793,0.0001955993,0.0003825773,0.0001090362,0.0003919379,0.0002610445,0.0002730429,0.0000834319,0.0002936319],"category_scores_gemma":[0.0003479913,0.00008312493,0.0001841594,0.004555041,0.000056244,0.0002785597,0.0004660962,0.0001856294,0.0000363816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000184801,"about_ca_system_score_gemma":0.00001358822,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004156019,"about_ca_topic_score_gemma":0.01123938,"domain_scores_codex":[0.9967746,0.0001325302,0.0005873763,0.00107935,0.0008520554,0.0005740463],"domain_scores_gemma":[0.9990078,0.00004065428,0.0001503736,0.000136126,0.0002196588,0.0004453663],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003820762,0.0001054586,0.6175324,0.000009356553,0.00002486916,0.0003680623,0.000981865,0.001724624,0.3562698,0.00001112494,0.001080504,0.02185378],"study_design_scores_gemma":[0.00007081322,0.00009126833,0.9920603,0.00002075305,0.00002512897,0.00000642698,0.0002434448,0.0008928382,0.005489463,0.0001554666,0.0007236628,0.0002204452],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971821,0.0000597509,0.000005226567,0.001642164,0.0004262637,0.0005189151,0.00003486217,0.00003733974,0.00009335834],"genre_scores_gemma":[0.9989918,0.00001235909,0.00008376663,0.000227212,0.0001040862,0.00002807633,0.0002453253,0.000001018532,0.0003063555],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3745279,"threshold_uncertainty_score":0.6282685,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07253409443635513,"score_gpt":0.2797025306702475,"score_spread":0.2071684362338924,"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."}}