{"id":"W2473126907","doi":"10.17707/agricultforest.62.2.24","title":"IMPACT OF CLIMATE FACTORS ON YIELD AND QUALITY OF VINE VARIETY CABERNET SAUVIGNON IN PODGORICA WINE GROWING REGION","year":2016,"lang":"en","type":"article","venue":"The Journal Agriculture and Forestry","topic":"Horticultural and Viticultural Research","field":"Agricultural and Biological Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Impact","funders":"","keywords":"Vine; Wine; Yield (engineering); Terroir; Quality (philosophy); Wine grape; Grape wine; Variety (cybernetics); Crop yield; Agronomy; Horticulture; Environmental science; Biology; Mathematics; Food science; Statistics","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":[0.000148166,0.0001594027,0.0001723095,0.0003394815,0.000277272,0.000361595,0.0001133403,0.0001281418,0.0005416258],"category_scores_gemma":[0.0001883312,0.00006756286,0.0001636718,0.0002919802,0.0001340819,0.0001175479,0.0001587358,0.0001269914,0.00005428321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000488243,"about_ca_system_score_gemma":0.0002065632,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02060624,"about_ca_topic_score_gemma":0.05022414,"domain_scores_codex":[0.9999013,0.00002126372,0.000005498805,0.00003802311,0.00001533512,0.00001856169],"domain_scores_gemma":[0.9998226,0.0000372754,0.00004506363,0.00000843397,0.00003489635,0.00005173508],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000272332,0.00007784138,0.9762148,0.00002505893,0.0000655799,0.000343505,0.0004095274,0.0005026318,0.01880523,0.00003998857,0.0001242695,0.003119207],"study_design_scores_gemma":[7.838914e-7,0.00002654392,0.9995566,8.452123e-7,0.00000321101,0.00002442292,0.0001131309,0.00008016203,0.0001219235,0.000003204788,0.0000682269,9.483034e-7],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997801,0.00003001569,0.00001047248,0.000004161846,9.645306e-7,5.023193e-7,0.00005753915,0.000001057391,0.0001151443],"genre_scores_gemma":[0.999638,0.00002325978,0.00001873467,0.000003275464,0.000001565703,0.000001326862,0.0001805448,7.934867e-7,0.0001325786],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02060624,"threshold_uncertainty_score":0.04097259,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04942244129232117,"score_gpt":0.292683460448403,"score_spread":0.2432610191560819,"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."}}