{"id":"W1908447211","doi":"10.1007/978-3-540-92706-8_6","title":"Functional Relationships Between Old-Growth Forest Canopies, Understorey Light and Vegetation Dynamics","year":2009,"lang":"en","type":"book-chapter","venue":"Ecological studies","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":24,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Understory; Biome; Vegetation (pathology); Taiga; Boreal; Ecology; Temperate rainforest; Temperate climate; Environmental science; Temperate forest; Canopy; Geography; Ecosystem; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003383996,0.0003821961,0.0005408921,0.00007057104,0.001081804,0.00002224327,0.0001232661,0.0005179808,0.0002461588],"category_scores_gemma":[0.0004198035,0.0003173888,0.00009828385,0.00005838777,0.0006128376,0.0001277578,0.0003118866,0.0006183646,0.0003655664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000877271,"about_ca_system_score_gemma":0.00001460824,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001168044,"about_ca_topic_score_gemma":0.01321724,"domain_scores_codex":[0.9983799,0.00006518619,0.000424988,0.0005736862,0.0002618274,0.0002944023],"domain_scores_gemma":[0.9986041,0.0008185011,0.0002732188,0.0001341472,0.00007465712,0.00009537267],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001982772,0.00005597665,0.5452939,0.00004996101,0.0005342187,0.00002211726,0.000441014,0.000445923,0.000001065045,0.4440195,0.007526899,0.00158959],"study_design_scores_gemma":[0.0001892634,0.0001905985,0.7044882,0.00002372626,0.0001470163,0.000003177831,0.0001143987,0.0001122945,2.141836e-7,0.2917465,0.002697675,0.0002869569],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.0501272,0.004558474,0.0004673819,0.01336913,0.0007554981,0.001040936,0.00004263183,0.0002690032,0.9293697],"genre_scores_gemma":[0.7703038,0.00200484,0.0005408531,0.0005576105,0.0002021252,0.0000552318,0.0001458256,0.00002898033,0.2261607],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.7201766,"threshold_uncertainty_score":0.9999278,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04832072021094218,"score_gpt":0.2349759325115762,"score_spread":0.186655212300634,"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."}}