{"id":"W4392464313","doi":"10.1111/jvs.13237","title":"Seedling recruitment in response to stand composition, interannual climate variability, and soil disturbance in the boreal mixed woods of Canada","year":2024,"lang":"en","type":"article","venue":"Journal of Vegetation Science","topic":"Forest Ecology and Biodiversity Studies","field":"Agricultural and Biological Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; Université du Québec en Abitibi-Témiscamingue","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Boreal; Disturbance (geology); Seedling; Taiga; Ecology; Environmental science; Geography; Agronomy; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003220038,0.00004005389,0.00009196582,0.00003915785,0.0001192062,0.0000394269,0.0001581201,0.00001443738,0.000001605367],"category_scores_gemma":[0.0001873761,0.00001457719,0.00001472963,0.0005417009,0.0001487285,0.000169773,0.00004623974,0.00008360984,1.688462e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009447813,"about_ca_system_score_gemma":0.00009745913,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001601765,"about_ca_topic_score_gemma":0.05443874,"domain_scores_codex":[0.9992012,0.0001467809,0.0002133696,0.00009557817,0.0002322085,0.0001108363],"domain_scores_gemma":[0.999224,0.0005581159,0.00006715901,0.00001703153,0.0001035443,0.00003015689],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001866478,0.0002810381,0.8505895,0.0001231372,0.0000257935,0.0001749544,0.02561748,0.001772786,0.1024898,0.001398549,0.0008316097,0.01482887],"study_design_scores_gemma":[0.00007430936,0.0002302319,0.9969404,0.00009695005,0.00000315857,0.00001238988,0.001608682,0.000143051,0.0004473827,0.0001962501,0.0002169447,0.00003021631],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9933008,0.0001500755,0.000004867572,0.006220877,0.0001592649,0.00008859231,0.00001102665,0.000001151674,0.00006333536],"genre_scores_gemma":[0.9997639,0.00002675135,0.00006897584,0.0001219275,0.00001365992,0.000001400996,3.746596e-7,1.019934e-7,0.00000292059],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.146351,"threshold_uncertainty_score":0.9628153,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02580530218764106,"score_gpt":0.2677524439566258,"score_spread":0.2419471417689847,"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."}}