{"id":"W7099485482","doi":"","title":"Recovery of late-seral vascular plants in a chronosequence of post-clearcut","year":2003,"lang":"en","type":"article","venue":"","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Clearcutting; Chronosequence; Species richness; Understory; Vegetation (pathology); Abundance (ecology); Ecological succession; Canopy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0002880341,0.0001780062,0.0001556139,0.0005328984,0.0003276705,0.0004370869,0.0002410672,0.0001867293,0.0005556592],"category_scores_gemma":[0.000614479,0.0001423393,0.0001205404,0.0002816315,0.0003579492,0.0001822352,0.0002692393,0.0002301837,0.0001270762],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006157201,"about_ca_system_score_gemma":0.0004071619,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.06238715,"about_ca_topic_score_gemma":0.2384062,"domain_scores_codex":[0.9998808,0.00001307085,0.000006872658,0.00003407761,0.00002378776,0.00004127234],"domain_scores_gemma":[0.9992373,0.00006343208,0.0003354535,0.00004647026,0.0001267455,0.0001906013],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001841145,0.0000430043,0.9888722,0.00001317954,0.00002193845,0.0001812644,0.0004888896,0.00004638287,0.007612331,0.00001310979,0.0000442955,0.002479304],"study_design_scores_gemma":[5.275157e-7,0.00001084313,0.9998631,6.161733e-7,8.637896e-7,0.00001411462,0.00004289912,0.00001037217,0.00002899866,8.002947e-7,0.00002643614,3.156718e-7],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9997999,0.00005974838,0.000009363919,0.000003288747,6.844419e-7,0.000001312044,0.00004811405,7.00184e-7,0.00007683135],"genre_scores_gemma":[0.9995506,0.00004162151,0.00003311739,0.000006687406,0.000001782309,0.000001726276,0.0001930519,5.677739e-7,0.0001707607],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06238715,"threshold_uncertainty_score":0.124048,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007204106534652772,"score_gpt":0.2116000194328077,"score_spread":0.2043959128981549,"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."}}