{"id":"W2991151531","doi":"10.3390/f10121074","title":"Autoregressive Modeling of Forest Dynamics","year":2019,"lang":"en","type":"article","venue":"Forests","topic":"Forest ecology and management","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Simons Foundation","keywords":"Autoregressive model; STAR model; Econometrics; Markov chain; Mean reversion; Statistics; Bayesian probability; Random walk; Basal area; Time series; Mathematics; Computer science; Autoregressive integrated moving average; Ecology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0000956375,0.00007908932,0.0001073698,0.00002636462,0.0000326292,0.000004328342,0.0001976434,0.00005651409,0.001344231],"category_scores_gemma":[0.00001357624,0.00006916677,0.00004334394,0.00006777295,0.00007617089,0.0001152446,0.0002091016,0.00006183463,0.00116354],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008500936,"about_ca_system_score_gemma":0.000005364018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001966495,"about_ca_topic_score_gemma":0.01121027,"domain_scores_codex":[0.9993526,0.00001139558,0.0001371025,0.0001713513,0.000140088,0.000187421],"domain_scores_gemma":[0.9996432,0.00001590039,0.00006429981,0.0002335494,0.000005113939,0.00003791861],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000104689,0.00002569953,0.6293342,0.0000105532,0.000006927738,0.00000273577,0.00005714664,0.3414455,0.000004631817,0.02850171,0.000401796,0.0001985945],"study_design_scores_gemma":[0.0001664813,0.00006057707,0.3653755,0.0000106271,0.000005930216,0.00000116277,0.00002219304,0.6161444,0.00001037442,0.01789281,0.0002434914,0.00006645222],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9522684,0.000008724391,0.006213517,0.00007005384,0.0002089467,0.0002145303,0.000003133865,0.00002478846,0.04098786],"genre_scores_gemma":[0.996788,0.000002503797,0.0004965804,0.00005021227,0.000008968073,0.000009840683,0.00001210946,0.000009043038,0.00262277],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2746989,"threshold_uncertainty_score":0.9996142,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005038971384062152,"score_gpt":0.2055150204943448,"score_spread":0.2004760491102827,"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."}}