{"id":"W4286209960","doi":"10.1111/ecog.06030","title":"Modelling seasonal dynamics of secondary growth in R","year":2022,"lang":"en","type":"article","venue":"Ecography","topic":"Plant Water Relations and Carbon Dynamics","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Chicoutimi","funders":"Javna Agencija za Raziskovalno Dejavnost RS","keywords":"Overfitting; Gompertz function; Tree (set theory); Xylem; Function (biology); Bayesian probability; Ecology; Computer science; Mathematics; Biological system; Environmental science; Statistics; Artificial neural network; Machine learning; Biology; Botany","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":[0.0001381514,0.00005228576,0.0000699001,0.00009213744,0.00005930635,0.000004128143,0.0001291608,0.00001690259,0.001018859],"category_scores_gemma":[7.29144e-7,0.00005742417,0.00005636964,0.0004386247,0.00004146426,0.00006879937,0.0001266456,0.0001529792,0.000005756825],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000598414,"about_ca_system_score_gemma":0.000005548458,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003205466,"about_ca_topic_score_gemma":0.0001416827,"domain_scores_codex":[0.9994434,0.00002843923,0.000122916,0.0001257586,0.000162459,0.0001170174],"domain_scores_gemma":[0.9998472,0.00001356447,0.00003925255,0.00007300565,0.000001702461,0.00002525583],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000006287875,0.00004859065,0.3741237,0.000002571641,0.000004274723,0.000004498802,0.0001128786,0.6235865,0.00002153855,0.001410653,0.00004756541,0.0006310298],"study_design_scores_gemma":[0.0001385541,0.00002328975,0.0187066,0.000001670176,0.000003247319,0.000005534395,0.00004465286,0.9722397,0.000008380039,0.008396798,0.0003532812,0.00007829447],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9801167,0.00002615557,0.001623273,0.00005656736,0.00005288783,0.00005532703,0.0001095699,0.00001053673,0.01794905],"genre_scores_gemma":[0.9988093,0.00001283041,0.000979312,0.00003288126,0.000002655739,0.00001140611,0.00006873147,0.000005521489,0.00007731656],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3554171,"threshold_uncertainty_score":0.9998943,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004714379599462928,"score_gpt":0.1654920889670268,"score_spread":0.1607777093675639,"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."}}