{"id":"W2109239173","doi":"10.1139/cjfr-2012-0402","title":"Improving tree selection for partial cutting through joint probability modelling of tree vigor and quality","year":2013,"lang":"en","type":"article","venue":"Canadian Journal of Forest Research","topic":"Forest ecology and management","field":"Environmental Science","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Fonds de recherche du Québec – Nature et technologies","keywords":"Beech; Hardwood; Yellow birch; Mathematics; Diameter at breast height; Tree (set theory); Joint probability distribution; Copula (linguistics); Forestry; Maple; Statistics; Botany; Biology; Geography; Econometrics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002951778,0.00008340539,0.0001900296,0.0001135909,0.0003343056,0.00005141981,0.0001896862,0.00007809743,0.0002687981],"category_scores_gemma":[0.0004954132,0.00007233285,0.0000690949,0.000195637,0.0004599408,0.0004340504,0.00005726772,0.0002913019,0.000008942118],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003697989,"about_ca_system_score_gemma":0.0002327019,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.09181689,"about_ca_topic_score_gemma":0.3184521,"domain_scores_codex":[0.9984119,0.0001701646,0.0004506959,0.0001896487,0.0002722722,0.0005053542],"domain_scores_gemma":[0.9990734,0.0001539537,0.0001899431,0.0001284373,0.0001451989,0.0003090318],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001281498,0.0001101473,0.8977023,0.0002903093,0.00006942364,0.000007527058,0.001918113,0.04558093,0.002367001,0.01978403,0.002769963,0.02927204],"study_design_scores_gemma":[0.001398076,0.001523159,0.7248157,0.00008031852,0.0000352084,0.00002762598,0.0007829014,0.1024268,0.004042058,0.1623826,0.002210097,0.0002755376],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9668359,0.00004106084,0.03044888,0.0005984787,0.0000690808,0.0006083078,0.000002819328,0.00000274963,0.001392724],"genre_scores_gemma":[0.990862,0.000006263017,0.008831326,0.00002295495,0.0000620816,0.00003469888,9.475355e-7,0.000008474721,0.0001712193],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2266353,"threshold_uncertainty_score":0.9142308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1144347309899082,"score_gpt":0.3140081854156635,"score_spread":0.1995734544257554,"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."}}