{"id":"W2325604464","doi":"10.5849/forsci.10-092","title":"A Generalized Mixed Logistic Model for Predicting Individual Tree Survival Probability with Unequal Measurement Intervals","year":2013,"lang":"en","type":"article","venue":"Forest Science","topic":"Forest ecology and management","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"Government of Alberta","funders":"Forest Resource Improvement Association of Alberta; Government of Alberta","keywords":"Basal area; Statistics; Pinus contorta; Mathematics; Logistic regression; Deciduous; Tree (set theory); Random effects model; Range (aeronautics); Population; Generalized linear model; Forestry; Ecology; Demography; Geography; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.01108212,0.001493164,0.002075692,0.001728429,0.0008567721,0.001822275,0.005286299,0.002399445,0.003006743],"category_scores_gemma":[0.03176586,0.001519455,0.002385919,0.001960666,0.0009319169,0.002561605,0.002366838,0.002571758,0.001128682],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001201687,"about_ca_system_score_gemma":0.001362301,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007120667,"about_ca_topic_score_gemma":0.006429632,"domain_scores_codex":[0.9947867,0.003191465,0.0002718668,0.001074582,0.0003985922,0.0002767083],"domain_scores_gemma":[0.9762307,0.0196232,0.001059678,0.00161539,0.001120182,0.0003507078],"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":[0.002953975,0.0005121936,0.03972592,0.0003142804,0.001105634,0.0006538124,0.0003838514,0.768896,0.002180686,0.02036502,0.003323521,0.1595851],"study_design_scores_gemma":[0.00003827867,0.0001112375,0.001340072,0.00001155624,0.00006267887,0.00006906351,0.00001656816,0.9930874,0.0001438961,0.004823105,0.0002692723,0.00002688993],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1233554,0.0004437109,0.8728401,0.0003665359,0.0001262644,0.0001570703,0.001099458,0.001060798,0.0005505586],"genre_scores_gemma":[0.7301514,0.0003478068,0.2601789,0.0002179168,0.0001976862,0.001105677,0.002668943,0.0002769467,0.004854815],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01108212,"threshold_uncertainty_score":0.05860853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08104302760424077,"score_gpt":0.2579523025625177,"score_spread":0.176909274958277,"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."}}