{"id":"W2128068485","doi":"10.5589/m10-052","title":"Identifying leading species using tree crown metrics derived from very high spatial resolution imagery in a boreal forest environment","year":2010,"lang":"en","type":"article","venue":"Canadian Journal of Remote Sensing","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Space Agency","keywords":"Crown (dentistry); Tree (set theory); Geography; Taiga; Cartography; Black spruce; Forestry; Remote sensing; Physical geography; Ecology; Mathematics; Biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005000425,0.0001966376,0.0002978744,0.0004578565,0.0003345917,0.0001745243,0.0001971998,0.0001473142,0.0000812977],"category_scores_gemma":[0.0002257178,0.000211091,0.0001202237,0.0004084211,0.0003181842,0.0003020189,0.0000469856,0.0006577412,0.00003491951],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009856363,"about_ca_system_score_gemma":0.0001808706,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.2850608,"about_ca_topic_score_gemma":0.4703988,"domain_scores_codex":[0.9982366,0.00008742645,0.0005391883,0.0002867202,0.0003604962,0.0004895727],"domain_scores_gemma":[0.9987376,0.0001118278,0.0003620931,0.0003057625,0.00002651136,0.0004561747],"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":[0.0000376721,0.00001518691,0.01925712,0.000006023749,0.00003399843,0.0007552154,0.001749455,0.005900067,0.4269342,0.000008694154,0.0003051062,0.5449973],"study_design_scores_gemma":[0.0008260873,0.00004536353,0.8042519,0.0002169819,0.0001090129,0.0006237542,0.0006264885,0.1622334,0.01861667,0.001687619,0.01020424,0.0005585505],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8765764,0.00005242246,0.1210703,0.0002163579,0.000565128,0.00009284569,0.000006427708,0.000007335439,0.001412791],"genre_scores_gemma":[0.8070565,0.00001558765,0.1924705,0.00005403749,0.0003239074,8.496974e-9,0.000008073035,0.00002609697,0.00004526793],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7849948,"threshold_uncertainty_score":0.8608041,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02240044422479657,"score_gpt":0.2256910886101019,"score_spread":0.2032906443853053,"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."}}