{"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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004537445,0.00006118992,0.0001248965,0.000009194991,0.00007626206,0.000006760699,0.0003379927,0.00006709568,0.004953864],"category_scores_gemma":[0.00006673026,0.00004989655,0.00004000524,0.00001945309,0.0002762616,0.00005159482,0.0003982316,0.00006381888,0.0002335749],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003537516,"about_ca_system_score_gemma":0.000003173821,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007742437,"about_ca_topic_score_gemma":0.001476714,"domain_scores_codex":[0.9993909,0.00005281735,0.0001227607,0.0002049185,0.00007743869,0.0001511721],"domain_scores_gemma":[0.9994039,0.00001777518,0.0000638722,0.0004830684,0.000001697368,0.00002966373],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000198588,0.0001660712,0.9859763,0.000005452346,0.00002462825,0.00003651925,0.00006875372,0.003738129,0.001755146,0.00331166,0.002329253,0.002568203],"study_design_scores_gemma":[0.0001433991,0.00004118031,0.9822222,8.742651e-7,0.00001335975,0.000001438438,0.000005552255,0.0001458324,0.0004668352,0.01268353,0.004222213,0.00005358146],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9495607,0.00001172257,0.0003863048,0.0003254116,0.0000886936,0.0001359431,0.000001719258,0.000007586869,0.0494819],"genre_scores_gemma":[0.9971581,0.00001776767,0.001970711,0.0001024667,0.000007965311,0.00001978981,8.659634e-7,0.000002541602,0.0007197528],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04876215,"threshold_uncertainty_score":0.9959558,"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."}}