{"id":"W2803672705","doi":"10.1093/forsci/fxy013","title":"Climatic Effects on Site Productivity of Red Pine Plantations","year":2018,"lang":"en","type":"article","venue":"Forest Science","topic":"Forest ecology and management","field":"Environmental Science","cited_by":30,"is_retracted":false,"has_abstract":false,"ca_institutions":"Ontario Forest Research Institute; Ministry of Natural Resources and Forestry","funders":"","keywords":"Site index; Environmental science; Precipitation; Climate change; Productivity; Representative Concentration Pathways; Growing season; Physical geography; Climatology; Geography; Ecology; Climate model; Atmospheric sciences; Forestry; Meteorology; Biology; Geology","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":[0.0005022503,0.00006672035,0.0000781172,0.00006319644,0.0002648912,0.00001023697,0.0002771305,0.00001815413,0.0002406702],"category_scores_gemma":[0.0002245491,0.00005450162,0.00001669552,0.0005488773,0.001462585,0.0002491247,0.0001881674,0.00004489257,0.0009618025],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005954944,"about_ca_system_score_gemma":0.00001315007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005491663,"about_ca_topic_score_gemma":0.0005887572,"domain_scores_codex":[0.9990802,0.00002303477,0.000105608,0.0002823697,0.0002787326,0.0002300599],"domain_scores_gemma":[0.9995123,0.0000532613,0.00007112635,0.0002976606,0.0000114759,0.00005414902],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001665599,0.0008171457,0.5474061,0.000132305,0.00001658609,0.00002003658,0.002120302,0.01615434,0.09656388,0.3202861,0.01305237,0.003264275],"study_design_scores_gemma":[0.0001624915,0.0005434641,0.9624794,0.00001996309,0.000007383122,0.000002230199,0.000008367232,0.002896226,0.01084987,0.02250162,0.0004489799,0.0000800438],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9826057,0.000001050646,0.00192407,0.0003149312,0.0002730721,0.0002804638,0.000001867643,0.00002352194,0.0145753],"genre_scores_gemma":[0.998405,0.000001049125,0.001041377,0.0001317557,0.00003207808,0.0000178969,0.000001574172,0.000003034542,0.0003662181],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4150732,"threshold_uncertainty_score":0.9998161,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006544411477777156,"score_gpt":0.2335187393367107,"score_spread":0.2269743278589335,"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."}}