{"id":"W4247845444","doi":"10.1111/j.1654-1103.2002.tb02080.x","title":"Structure and composition of edges next to regenerating clear‐cuts in mixed‐wood boreal forest","year":2002,"lang":"en","type":"article","venue":"Journal of Vegetation Science","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":115,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Snag; Taiga; Secondary forest; Old-growth forest; Understory; Shrub; Ecology; Coarse woody debris; Boreal; Canopy; Regeneration (biology); Biology; Forestry; Geography; Habitat","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004597105,0.00005992845,0.0001239455,0.0001521256,0.0001444014,0.00002933461,0.0001411983,0.00002905927,0.00001950593],"category_scores_gemma":[0.0001411104,0.00005104313,0.00001815167,0.0004646846,0.0003186816,0.0006402998,0.00005892288,0.00009852029,0.00000450691],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006678598,"about_ca_system_score_gemma":0.0000111839,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001147273,"about_ca_topic_score_gemma":0.0005742087,"domain_scores_codex":[0.9990985,0.00004005749,0.0003192892,0.0001227508,0.0002954107,0.0001239956],"domain_scores_gemma":[0.999477,0.00007167914,0.0002615388,0.00005729454,0.00006675175,0.00006579295],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003114526,0.0001029999,0.693146,0.0000225819,0.000008330507,0.000008039183,0.007456087,0.1262415,0.1457195,0.002410449,0.0001458216,0.02470757],"study_design_scores_gemma":[0.0002266217,0.0002035826,0.9739075,0.00003592511,0.000005496606,0.00003613863,0.0001902784,0.01941629,0.005193215,0.000717953,0.00001032586,0.00005672741],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974779,0.0001681397,0.0006979515,0.0005168162,0.0001350371,0.00006345834,7.106769e-7,0.000002041977,0.0009378915],"genre_scores_gemma":[0.9924192,0.00003841949,0.007382561,0.0001231702,0.0000202102,7.488218e-7,2.499883e-7,0.000002416454,0.00001306493],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2807615,"threshold_uncertainty_score":0.2081478,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01730865749537403,"score_gpt":0.2518561037191895,"score_spread":0.2345474462238155,"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."}}