{"id":"W2146002208","doi":"10.1139/x07-109","title":"Forest-level analyses of uneven-aged hardwood forests","year":2008,"lang":"en","type":"article","venue":"Canadian Journal of Forest Research","topic":"Forest ecology and management","field":"Environmental Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Ministry of Natural Resources","keywords":"Basal area; Maple; Beech; Hardwood; Forest management; Ecology; Diversity (politics); Forestry; Old-growth forest; Residual; Mathematics; Geography; Environmental science; Agroforestry; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003989162,0.0001179856,0.0001953908,0.0005206334,0.0003060262,0.0004366132,0.0002796996,0.0001231542,0.00195103],"category_scores_gemma":[0.001167581,0.00009945595,0.0003146149,0.0006433284,0.0001970717,0.0002856451,0.0003322462,0.0001829565,0.0001321521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001155397,"about_ca_system_score_gemma":0.0004498074,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.07382314,"about_ca_topic_score_gemma":0.192548,"domain_scores_codex":[0.9998224,0.0000411966,0.000008869019,0.00003726192,0.00003651989,0.00005381233],"domain_scores_gemma":[0.9993502,0.0002377401,0.0001125472,0.00005662543,0.0001531636,0.00008964782],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003109887,0.00007720021,0.8874894,0.00008602972,0.0002034632,0.0002481689,0.0003970536,0.08346786,0.009915395,0.003907796,0.0003057271,0.01359086],"study_design_scores_gemma":[0.000007989167,0.00003284266,0.9266966,0.000004862321,0.00003750961,0.00004934892,0.0002475238,0.07071462,0.0005420335,0.00118314,0.0004742882,0.000009236246],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9983237,0.00004409136,0.0008937971,0.00000534737,4.872521e-7,0.000003323007,0.0002418219,0.000009180052,0.0004783456],"genre_scores_gemma":[0.9989145,0.00001203999,0.0006073995,0.000001984079,7.132357e-7,0.000002610538,0.0003025746,0.000002553304,0.0001556711],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07382314,"threshold_uncertainty_score":0.1467869,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1283256163455236,"score_gpt":0.3489890591680805,"score_spread":0.2206634428225569,"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."}}