{"id":"W2116799252","doi":"10.1109/igarss.2007.4422887","title":"Spatial distribution mapping of vegetation cover in urban environment using tdvi for quality of life monitoring","year":2007,"lang":"en","type":"article","venue":"","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Normalized Difference Vegetation Index; Vegetation (pathology); Environmental science; Enhanced vegetation index; Remote sensing; Ground truth; Satellite; Vegetation Index; Physical geography; Leaf area index; Geography; Computer science","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":[0.0002678449,0.0001333216,0.0001016467,0.001083794,0.00008052589,0.0002338933,0.0001481202,0.00006746229,0.0004200946],"category_scores_gemma":[0.0005098532,0.00006155948,0.0001121944,0.0009518975,0.00009510687,0.0001467817,0.0001131185,0.0000780563,0.0001017919],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003128866,"about_ca_system_score_gemma":0.000160676,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01014762,"about_ca_topic_score_gemma":0.01759635,"domain_scores_codex":[0.9999021,0.00003086223,0.000003807603,0.0000171136,0.00003532431,0.00001080062],"domain_scores_gemma":[0.9998015,0.0000483893,0.00003857879,0.00002297261,0.00007097927,0.00001757646],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003900114,0.0001401839,0.6421509,0.0001391606,0.0001538846,0.0001560772,0.0003317251,0.03645588,0.06257629,0.0007011894,0.0008581441,0.2559466],"study_design_scores_gemma":[0.00001453148,0.0001258837,0.8340227,0.000008910674,0.00005055988,0.0001402105,0.0001801965,0.1535754,0.01009387,0.0002912413,0.00148087,0.00001556967],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.968527,0.0001112766,0.02887942,0.00003461658,0.000003865442,0.00003064252,0.0007458196,0.0001910928,0.001476385],"genre_scores_gemma":[0.9843514,0.00005566938,0.01456308,0.00000358542,0.000002405005,0.00001305496,0.0007056602,0.000008277988,0.000296914],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01014762,"threshold_uncertainty_score":0.02017713,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02991064758228227,"score_gpt":0.2651081859500841,"score_spread":0.2351975383678019,"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."}}