{"id":"W2184834289","doi":"","title":"THE EFFECT OF FOUR NEW MULTISPECTRAL BANDS OF WORLDVIEW2 ON IMPROVING URBAN LAND COVER CLASSIFICATION","year":2012,"lang":"en","type":"article","venue":"","topic":"Remote-Sensing Image Classification","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Impervious surface; Land cover; Multispectral image; Spectral bands; Remote sensing; Pattern recognition (psychology); Contextual image classification; Feature (linguistics); Data set; Computer science; Artificial intelligence; Set (abstract data type); Class (philosophy); Geography; Image (mathematics); Land use; Engineering","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001320406,0.0009959228,0.0004284583,0.001121944,0.0002334655,0.0007018727,0.0004330598,0.0005436759,0.0006149629],"category_scores_gemma":[0.003375169,0.0002223419,0.0006030196,0.0007328822,0.0003043082,0.0009828364,0.0006133594,0.0004818146,0.0002898042],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001938661,"about_ca_system_score_gemma":0.0002060589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002348174,"about_ca_topic_score_gemma":0.004734659,"domain_scores_codex":[0.9992848,0.000185353,0.00005055471,0.0001480093,0.0002403372,0.00009090593],"domain_scores_gemma":[0.9984285,0.0008347374,0.0001525137,0.0001905789,0.0003119483,0.00008169757],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002631054,0.0008284869,0.04401752,0.0004998915,0.0003859125,0.0002741616,0.0002703868,0.05574978,0.306893,0.000355434,0.00162568,0.5864687],"study_design_scores_gemma":[0.0001724199,0.001766808,0.2932184,0.00006995499,0.0007808879,0.000595662,0.0004398204,0.3739697,0.3210886,0.0004594804,0.007280234,0.0001580017],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9289508,0.001034818,0.06649687,0.000145432,0.0001176987,0.0001294872,0.0003245515,0.0006625195,0.00213782],"genre_scores_gemma":[0.8312888,0.0006545797,0.1657729,0.00009382347,0.00005274999,0.00004998438,0.0009848444,0.0001081297,0.0009942844],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.002348174,"threshold_uncertainty_score":0.006983042,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01501676058080853,"score_gpt":0.2280172848277662,"score_spread":0.2130005242469577,"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."}}