{"id":"W2768061235","doi":"10.2298/gensr1702529b","title":"Morphological variability of Quercus robur L. leaf in Serbia","year":2017,"lang":"en","type":"article","venue":"Genetika","topic":"Forest ecology and management","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute for Biological Sciences","funders":"Ministarstvo Prosvete, Nauke i Tehnološkog Razvoja","keywords":"Intraspecific competition; Quercus robur; Biology; Population; Genetic variability; Multivariate analysis of variance; Discriminant function analysis; Analysis of variance; Multivariate statistics; Botany; Horticulture; Zoology; Statistics; Mathematics; Demography","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":[0.0004069527,0.0002825169,0.0002819454,0.001128543,0.0002851849,0.0003316895,0.000159027,0.0001496258,0.000410968],"category_scores_gemma":[0.0002684173,0.0001109973,0.000169371,0.0003387927,0.000245318,0.0001128993,0.0001987504,0.000120231,0.0001351386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00017682,"about_ca_system_score_gemma":0.00008353371,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004876471,"about_ca_topic_score_gemma":0.01445894,"domain_scores_codex":[0.999772,0.00006270701,0.00001487054,0.00007577894,0.00004465503,0.00002991713],"domain_scores_gemma":[0.9998006,0.00004683325,0.0000720819,0.00002339867,0.00003161199,0.00002551596],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004700125,0.0001999844,0.8873199,0.00007968414,0.0001329694,0.0005763884,0.001551782,0.0005644544,0.07778987,0.0001568657,0.0001706271,0.03098748],"study_design_scores_gemma":[0.000002658764,0.0000705815,0.9989468,0.00000418388,0.000007696836,0.0002007857,0.0001734065,0.0001200373,0.0002832742,0.00000929143,0.0001787277,0.00000248812],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995628,0.0001215555,0.00008072957,0.000002219346,0.000001189603,0.000001876655,0.00004917385,0.000002282793,0.0001780999],"genre_scores_gemma":[0.9994,0.00005377493,0.000215652,0.000004798409,0.000001843731,0.000002834322,0.000167448,0.000002544821,0.0001511172],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004876471,"threshold_uncertainty_score":0.009696186,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01280738805373111,"score_gpt":0.2360438689306951,"score_spread":0.223236480876964,"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."}}