{"id":"W2076461495","doi":"10.1016/s0378-1127(01)00741-1","title":"Maximum size–density relationship for constraining individual tree mortality functions","year":2002,"lang":"en","type":"article","venue":"Forest Ecology and Management","topic":"Forest ecology and management","field":"Environmental Science","cited_by":44,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Statistics; Mathematics; Maximum density; Probability density function; Boreal; Density dependence; Thinning; Ecology; Function (biology); Tree (set theory); Biology; Demography; Physics; Mathematical analysis","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":[0.0004624651,0.0001591744,0.0001654717,0.00005803378,0.0005984156,0.00002511583,0.0001596886,0.0001292539,0.002161546],"category_scores_gemma":[0.0000871066,0.0001624628,0.00006326224,0.0001268611,0.0004546382,0.0001580781,0.0003432965,0.0001223571,0.00045342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006739931,"about_ca_system_score_gemma":0.00000215369,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002155382,"about_ca_topic_score_gemma":0.004655679,"domain_scores_codex":[0.9987855,0.0000530673,0.0002373639,0.0004182142,0.0001170526,0.0003888204],"domain_scores_gemma":[0.9993163,0.0002571353,0.00009135171,0.0002370721,0.000006246963,0.00009186193],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000201082,0.0001841305,0.7979004,0.00003752846,0.0001622651,0.00002561358,0.0001742364,0.0005973171,8.284738e-7,0.1424569,0.05578188,0.002658812],"study_design_scores_gemma":[0.0008157013,0.0001656708,0.9106976,0.000003322311,0.0001928466,0.000006538785,0.0001904066,0.0008336628,8.75893e-7,0.05866051,0.02827193,0.0001609376],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8853142,0.0000283264,0.00630835,0.001742051,0.0006484108,0.001470842,0.00002766978,0.0001298634,0.1043303],"genre_scores_gemma":[0.9883998,0.00003686855,0.003061952,0.001028929,0.00002518662,0.0003459785,0.00003514861,0.00001050431,0.007055606],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1127972,"threshold_uncertainty_score":0.9987506,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03229175598155788,"score_gpt":0.2331821040902659,"score_spread":0.200890348108708,"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."}}