{"id":"W4412464339","doi":"10.1016/j.foreco.2025.122987","title":"A new lens on biodiversity assessment: The reliability of high-resolution remote sensing in investigating tree species diversity in old-growth forests","year":2025,"lang":"en","type":"article","venue":"Forest Ecology and Management","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Instytut Badawczy Leśnictwa; Narodowe Centrum Badań i Rozwoju; Innovation for Defence Excellence and Security","keywords":"Biodiversity; Diversity (politics); Tree (set theory); Ecology; Reliability (semiconductor); Geography; Species diversity; Agroforestry; Remote sensing; Environmental resource management; Environmental science; Biology; Mathematics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0266836,0.001328423,0.001258971,0.008703491,0.001716325,0.01254964,0.001789226,0.00274798,0.00262976],"category_scores_gemma":[0.0369863,0.0006720979,0.00081448,0.00444028,0.01501555,0.01921583,0.006183826,0.005137349,0.0006060982],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001766012,"about_ca_system_score_gemma":0.001341375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007181055,"about_ca_topic_score_gemma":0.00876814,"domain_scores_codex":[0.9890344,0.005993232,0.0006217381,0.001727742,0.002340236,0.0002826881],"domain_scores_gemma":[0.9398499,0.04599606,0.004344207,0.004959235,0.003950405,0.000900229],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0004680484,0.0001630262,0.1229119,0.002952253,0.0007951672,0.0009363277,0.02733331,0.006761239,0.01607224,0.3232554,0.01110095,0.4872501],"study_design_scores_gemma":[0.00008134089,0.0009071693,0.1842363,0.00655372,0.0006228678,0.003475307,0.03466694,0.02690091,0.01171383,0.5655401,0.1646677,0.0006337358],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1466973,0.1059729,0.6115101,0.05744056,0.003125674,0.0002275583,0.001849273,0.0007175954,0.07245914],"genre_scores_gemma":[0.8483156,0.01536389,0.1241046,0.005447888,0.003926557,0.0001535919,0.00023691,0.0002086463,0.002242306],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0266836,"threshold_uncertainty_score":0.141118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01293159978205205,"score_gpt":0.2214597352605639,"score_spread":0.2085281354785118,"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."}}