{"id":"W1953666938","doi":"10.1139/cjfr-2013-0179","title":"Modelling <i>Pinus pinea</i> forest management to attain natural regeneration under present and future climatic scenarios","year":2013,"lang":"en","type":"article","venue":"Canadian Journal of Forest Research","topic":"Forest Management and Policy","field":"Environmental Science","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Silviculture; Regeneration (biology); Forest management; Seed dispersal; Biological dispersal; Agroforestry; Woodland; Salvage logging; Natural regeneration; Environmental science; Climate change; Forest ecology; Ecology; Biology; Ecosystem; Population","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002914948,0.0003342005,0.0002700635,0.0002517152,0.0002602971,0.0007159946,0.0005355281,0.0005224026,0.0008658713],"category_scores_gemma":[0.0004585023,0.0001417814,0.0003966474,0.0002266752,0.0002477903,0.00025502,0.0002355318,0.0002285276,0.00009023684],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001071704,"about_ca_system_score_gemma":0.001292281,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07304697,"about_ca_topic_score_gemma":0.0696472,"domain_scores_codex":[0.9999086,0.00002626369,0.000003947099,0.00001962851,0.00001015368,0.00003150122],"domain_scores_gemma":[0.9998005,0.00007547939,0.00005412666,0.000008643375,0.00002576931,0.00003556022],"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":[0.00001373694,0.00001461457,0.00465274,0.00001993824,0.00001135372,0.00002836361,0.00001381468,0.9926972,0.0008520099,0.0006388173,0.00008655022,0.0009708848],"study_design_scores_gemma":[0.00000744025,0.0000310268,0.00460961,0.000006483198,0.00001036808,0.00001625996,0.00003617731,0.9940535,0.0001962488,0.0005358607,0.0004904238,0.000006581112],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9665548,0.0003439111,0.02491951,0.0002073386,0.0000193364,0.00003652938,0.0004228091,0.000108532,0.007387253],"genre_scores_gemma":[0.9968559,0.00007009236,0.002140891,0.00001240367,0.000002678775,0.00001737921,0.00006966876,0.00001007091,0.0008208549],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07304697,"threshold_uncertainty_score":0.1452436,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03043148555008,"score_gpt":0.278100159244304,"score_spread":0.247668673694224,"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."}}