{"id":"W1753464969","doi":"10.1111/j.1365-2664.2005.01124.x","title":"Application of a variance decomposition method to compare satellite and aerial inventory data: a tool for evaluating wildlife–habitat relationships","year":2006,"lang":"en","type":"article","venue":"Journal of Applied Ecology","topic":"Wildlife Ecology and Conservation","field":"Environmental Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Natural Resources and Forestry; Laurentian University","funders":"","keywords":"Woodland; Ordination; Understory; Vegetation (pathology); Wildlife; Woodland caribou; Habitat; Geography; Ecology; Forest inventory; Land cover; Environmental science; Forest management; Environmental resource management; Land use; Canopy; Forestry; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02379382,0.001703048,0.001622887,0.01135179,0.0008090105,0.001885143,0.001057774,0.0005535792,0.006005565],"category_scores_gemma":[0.04735336,0.000561043,0.001866609,0.007504573,0.0007773656,0.001246065,0.001290506,0.001524476,0.0009941601],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008224279,"about_ca_system_score_gemma":0.001312623,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00408062,"about_ca_topic_score_gemma":0.00333603,"domain_scores_codex":[0.9839552,0.009117732,0.001738058,0.001578352,0.003275126,0.0003353898],"domain_scores_gemma":[0.9492861,0.03776538,0.002896087,0.003408085,0.006298294,0.0003461141],"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":[0.001630662,0.001132262,0.3091138,0.001438913,0.004624685,0.0005312674,0.002561381,0.01542296,0.02262707,0.01293163,0.01539726,0.612588],"study_design_scores_gemma":[0.0003396211,0.003221011,0.6035289,0.0005567935,0.001090319,0.0009485757,0.003411889,0.3233879,0.01412138,0.02029087,0.02874409,0.0003586946],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2183777,0.0003451989,0.7625126,0.0001269735,0.0003173081,0.002590822,0.005903137,0.003227788,0.006598498],"genre_scores_gemma":[0.446008,0.00010722,0.5431684,0.00004806897,0.00007469655,0.005456937,0.003775929,0.0005240771,0.0008366873],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02379382,"threshold_uncertainty_score":0.1258353,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03919715059725035,"score_gpt":0.3236598062424718,"score_spread":0.2844626556452214,"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."}}