{"id":"W3134750445","doi":"10.1139/cjfr-2020-0244","title":"Quantifying the vertical diversification development stage of old-growth Douglas-fir to derive stage-specific targets for restoration silviculture","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Forest Research","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Diversification (marketing strategy); Silviculture; Stand development; Tree (set theory); Natural regeneration; Ecology; Forestry; Geography; Biology; Mathematics; Combinatorics","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":[0.0003108745,0.0002511461,0.0001563081,0.0006066354,0.0002881382,0.0004137651,0.0002093876,0.0001530254,0.0004616606],"category_scores_gemma":[0.0003289968,0.0001271511,0.00009885241,0.0002886351,0.0001834208,0.0002726551,0.0002365617,0.0001364271,0.00009024321],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004092822,"about_ca_system_score_gemma":0.0003059685,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009734936,"about_ca_topic_score_gemma":0.05262379,"domain_scores_codex":[0.9999126,0.000009165702,0.000005577696,0.00003862229,0.00002052686,0.00001345289],"domain_scores_gemma":[0.9998123,0.00003045459,0.00006763842,0.000009706785,0.00004941939,0.0000305116],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002231748,0.00008971855,0.7347338,0.0001092541,0.00003814639,0.00005659094,0.00066024,0.004692541,0.210473,0.000400465,0.0001775701,0.04834558],"study_design_scores_gemma":[0.000003574962,0.00008968834,0.9785453,0.00001135484,0.00001922305,0.00003868949,0.0002844137,0.008442359,0.01168068,0.0001288525,0.0007477169,0.000008169935],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942386,0.0001827755,0.004311366,0.000005433068,0.000002138689,0.00002178606,0.000151722,0.0000177968,0.001068389],"genre_scores_gemma":[0.9939313,0.00005698339,0.005551136,0.000004383627,0.000001228429,0.00001222383,0.0001505558,0.000004744526,0.0002875475],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9902651,"threshold_uncertainty_score":0.01935655,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08513381557431307,"score_gpt":0.3215172931777529,"score_spread":0.2363834776034398,"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."}}