{"id":"W2133969433","doi":"10.1139/x07-138","title":"How to find the rare trees in the forest — New inventory strategies for culturally modified trees in boreal Sweden","year":2008,"lang":"en","type":"article","venue":"Canadian Journal of Forest Research","topic":"Forest Ecology and Biodiversity Studies","field":"Agricultural and Biological Sciences","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Forest inventory; Sampling (signal processing); Taiga; Boreal; Geography; Distance sampling; Abundance (ecology); Forestry; Plot (graphics); Ecology; Physical geography; Forest management; Statistics; Mathematics; Computer science; Biology; Archaeology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.004209807,0.0003002681,0.0003385514,0.001339561,0.0004501418,0.0008895989,0.0006673049,0.0002681288,0.0003708021],"category_scores_gemma":[0.01132833,0.0002708464,0.0002951765,0.0009628972,0.0004542503,0.001111584,0.0005915448,0.0001961565,0.0001248429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006833936,"about_ca_system_score_gemma":0.001059674,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02704816,"about_ca_topic_score_gemma":0.0559919,"domain_scores_codex":[0.998235,0.001184468,0.0001188666,0.0001923376,0.0002135712,0.00005572421],"domain_scores_gemma":[0.9946818,0.002983251,0.0006280169,0.0007031531,0.0008183085,0.0001855637],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002681192,0.0001467213,0.5677739,0.0002176734,0.0001365011,0.0002628649,0.006326024,0.07579801,0.003585983,0.002148079,0.0009840766,0.342352],"study_design_scores_gemma":[0.0001011169,0.0009463435,0.4067627,0.0002141527,0.0002140096,0.001164591,0.01198349,0.5576401,0.005113294,0.009006048,0.006633453,0.0002206561],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9402878,0.0002153935,0.05745755,0.0002141651,0.00001068511,0.0001868057,0.0001532942,0.0001384783,0.001335868],"genre_scores_gemma":[0.8469228,0.0002294553,0.1520382,0.00002687102,0.000006321968,0.0001493718,0.0002221233,0.00002541337,0.0003795303],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02704816,"threshold_uncertainty_score":0.05378145,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.129355964839649,"score_gpt":0.2895605591585844,"score_spread":0.1602045943189355,"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."}}