{"id":"W2338138057","doi":"","title":"Q2 How wetland type and area differ through scale: A GEOBIA case study in Alberta's","year":2011,"lang":"en","type":"article","venue":"","topic":"Land Use and Ecosystem Services","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Wetland; Scale (ratio); Spatial ecology; Pixel; Thematic map; Environmental science; Cartography; Geography; Remote sensing; Boreal; Object based; Physical geography; Hydrology (agriculture); Ecology; Computer science; Geology; Artificial intelligence; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"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":[0.0004009783,0.0002468685,0.000156886,0.001135815,0.001994292,0.001384866,0.0005889272,0.0004713637,0.001098815],"category_scores_gemma":[0.001044944,0.0001169434,0.0002146658,0.001940217,0.001146606,0.0003129749,0.0004806964,0.0002976203,0.000116869],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007957879,"about_ca_system_score_gemma":0.004043086,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9303521,"about_ca_topic_score_gemma":0.9799805,"domain_scores_codex":[0.9996992,0.00004260666,0.000007815849,0.00003935091,0.0001166599,0.00009435129],"domain_scores_gemma":[0.9995102,0.0001410752,0.0000444439,0.00003027482,0.0001947185,0.00007933551],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000584637,0.000445595,0.8070027,0.0002097984,0.00009918806,0.01221161,0.02207284,0.02147304,0.013605,0.006258765,0.007464611,0.1085721],"study_design_scores_gemma":[0.00002330848,0.00008846154,0.9087688,0.00005673332,0.00004280031,0.001186916,0.0488253,0.02462856,0.002510389,0.0008280199,0.01299337,0.00004733858],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9935634,0.00008181687,0.0007387229,0.0001998252,0.000003979969,0.00004502291,0.0005061789,0.00003113914,0.004829883],"genre_scores_gemma":[0.9939323,0.00008720433,0.00247261,0.00004880853,0.000002675845,0.00001073096,0.0004853305,0.0000107502,0.002949606],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06964791,"threshold_uncertainty_score":0.1401161,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02670757281603043,"score_gpt":0.2180536998316693,"score_spread":0.1913461270156389,"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."}}