{"id":"W2165606678","doi":"10.5589/m02-064","title":"Classification of wetland habitat and vegetation communities using multi-temporal Ikonos imagery in southern Saskatchewan","year":2002,"lang":"en","type":"article","venue":"Canadian Journal of Remote Sensing","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":93,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Habitat; Wetland; Vegetation (pathology); Transect; Normalized Difference Vegetation Index; Geography; Waterfowl; Wildlife; Land cover; Physical geography; Aerial survey; Ecology; Remote sensing; Environmental science; Land use; Climate change","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"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":[0.0003375114,0.0003674748,0.000191159,0.001601744,0.0009465741,0.0007238187,0.0006391567,0.0002331443,0.001149816],"category_scores_gemma":[0.0005037567,0.0002978389,0.0002004573,0.002531288,0.0005657457,0.000347784,0.0005258126,0.0002686767,0.0003822099],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007403252,"about_ca_system_score_gemma":0.007507635,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9629654,"about_ca_topic_score_gemma":0.9899212,"domain_scores_codex":[0.9997988,0.00002628902,0.00001611031,0.00004663257,0.00005417,0.0000579663],"domain_scores_gemma":[0.9995953,0.00004061657,0.00003398662,0.00002497103,0.0002284104,0.00007671665],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002697409,0.0001537474,0.9133207,0.0001064509,0.0001399432,0.00102703,0.002248616,0.003271046,0.01613253,0.0003287875,0.003068765,0.05993262],"study_design_scores_gemma":[0.00001398167,0.00001746996,0.9918972,0.00002464564,0.00002119617,0.00006227476,0.002617338,0.003637117,0.0005598801,0.0000445617,0.001085096,0.00001939011],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958182,0.00009803195,0.0003480666,0.0001017856,0.000003381671,0.00005857675,0.001489781,0.0000351744,0.002047008],"genre_scores_gemma":[0.9914582,0.000262261,0.001833706,0.00007473925,0.000002248127,0.00006450192,0.003132993,0.00001317251,0.003158078],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03703463,"threshold_uncertainty_score":0.07450539,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03059875599099576,"score_gpt":0.2195711695934011,"score_spread":0.1889724136024053,"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."}}