{"id":"W2009203701","doi":"10.1016/j.jag.2014.12.004","title":"Integrating optical satellite data and airborne laser scanning in habitat classification for wildlife management","year":2015,"lang":"en","type":"article","venue":"International Journal of Applied Earth Observation and Geoinformation","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":30,"is_retracted":false,"has_abstract":false,"ca_institutions":"Foothills Medical Centre; University of Alberta; University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Wildlife; Habitat; Multispectral image; Geography; Remote sensing; Canopy; Terrain; Cartography; Environmental resource management; Ecology; Environmental science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.0006732034,0.0002631038,0.0002345541,0.001814443,0.0003454649,0.0008838229,0.0003491111,0.0003293897,0.001284645],"category_scores_gemma":[0.001419081,0.0002185452,0.0002886174,0.001920079,0.0001828887,0.001237762,0.0004808148,0.0002464901,0.0004216458],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004216334,"about_ca_system_score_gemma":0.0007938782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02067543,"about_ca_topic_score_gemma":0.06861161,"domain_scores_codex":[0.9997063,0.00008312069,0.00002267836,0.00004275309,0.00010638,0.00003870558],"domain_scores_gemma":[0.9992316,0.0002190941,0.00009794775,0.00006169028,0.0003551957,0.00003447756],"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":[0.0001596575,0.0003587869,0.2475506,0.0001244026,0.0001807132,0.0001013741,0.0001977099,0.02424113,0.01961431,0.0008621922,0.002967608,0.7036415],"study_design_scores_gemma":[0.00004713795,0.0002845484,0.3810968,0.0001431707,0.000473473,0.0002113542,0.001364062,0.5852523,0.01822806,0.004085828,0.008737381,0.00007589054],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8531717,0.001415465,0.1325246,0.0005898472,0.0001579718,0.0001582933,0.001278854,0.0007297365,0.009973511],"genre_scores_gemma":[0.9153051,0.0004343397,0.08216456,0.00008683885,0.00003948348,0.00004008529,0.0005062112,0.00003186617,0.00139137],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02067543,"threshold_uncertainty_score":0.04111016,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04653510480808086,"score_gpt":0.2769744192219347,"score_spread":0.2304393144138538,"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."}}