{"id":"W2173164864","doi":"10.1139/x2012-142","title":"The effect of size and competition on tree growth rate in old-growth coniferous forests","year":2012,"lang":"en","type":"article","venue":"Canadian Journal of Forest Research","topic":"Forest ecology and management","field":"Environmental Science","cited_by":79,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Cancer Institute","keywords":"Competition (biology); Growth rate; Akaike information criterion; Ecology; Tree (set theory); Storage effect; Biology; Growth model; Statistics; Econometrics; Mathematics","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":[0.003227845,0.0005385931,0.0004657655,0.0006794073,0.000633701,0.0007746953,0.0006815295,0.0005461947,0.0006421048],"category_scores_gemma":[0.00618778,0.0004227127,0.0007471367,0.000454201,0.0009386967,0.0008612588,0.0004075288,0.0005396257,0.0001280318],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001636914,"about_ca_system_score_gemma":0.0008565717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1200658,"about_ca_topic_score_gemma":0.2201814,"domain_scores_codex":[0.9994119,0.0002062331,0.000037756,0.0001701505,0.00007297154,0.000101004],"domain_scores_gemma":[0.9946809,0.004042703,0.0004878633,0.0002188762,0.000193709,0.000375855],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003046381,0.00008098037,0.9482774,0.0000411036,0.0001288645,0.0001285155,0.0001825608,0.0425626,0.00218329,0.0004260183,0.0003224571,0.005361427],"study_design_scores_gemma":[0.00001744977,0.00007310321,0.9243678,0.00001095317,0.00005524348,0.00009652587,0.0001413181,0.07384668,0.0004214991,0.0007092217,0.0002336161,0.00002670878],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9991875,0.0001250283,0.0002886462,0.00003162336,0.000002268299,0.000001914237,0.0000786294,0.00001124645,0.0002730963],"genre_scores_gemma":[0.9994167,0.00004619706,0.0002361963,0.000006973968,0.000002669488,0.000002661176,0.0001854306,0.00000652513,0.00009668984],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1200658,"threshold_uncertainty_score":0.2387339,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01244335033635236,"score_gpt":0.2615147937506783,"score_spread":0.249071443414326,"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."}}