{"id":"W7098493078","doi":"","title":"www.mdpi.com/journal/remotesensing Article Spatial Enhancement of MODIS-based Images of Leaf Area Index: Application to the Boreal Forest Region of Northern","year":2010,"lang":"en","type":"article","venue":"","topic":"Historical Art and Culture Studies","field":"Arts and Humanities","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Leaf area index; Image resolution; Moderate-resolution imaging spectroradiometer; Spectroradiometer; Vegetation (pathology); Taiga; Canopy; Boreal; Tree canopy","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":[0.0005805428,0.0006135482,0.0004577774,0.00168186,0.000220984,0.001104225,0.0005621583,0.0007977365,0.01091562],"category_scores_gemma":[0.0004262422,0.0003093899,0.0007208075,0.001509142,0.000338552,0.000561262,0.0006371156,0.0002906304,0.01059649],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002655625,"about_ca_system_score_gemma":0.0005749163,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005210008,"about_ca_topic_score_gemma":0.004900181,"domain_scores_codex":[0.9996994,0.00005323091,0.00001751445,0.00004900767,0.0001565387,0.00002436805],"domain_scores_gemma":[0.9998331,0.00003157795,0.000023882,0.00003254742,0.00004815847,0.00003079704],"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":[0.0004439126,0.0007527789,0.01862362,0.0008488582,0.000264321,0.001304952,0.0001743059,0.05606002,0.1379464,0.001167731,0.03687137,0.7455417],"study_design_scores_gemma":[0.0001973898,0.0005687291,0.09140249,0.0002898052,0.0003548872,0.001443855,0.0006754908,0.751392,0.04275358,0.004204617,0.1064776,0.0002394607],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5567996,0.01199003,0.2621348,0.00439836,0.003256925,0.0006124967,0.01163072,0.02702174,0.1221554],"genre_scores_gemma":[0.7419941,0.004382163,0.218174,0.0007287978,0.0007480935,0.000186315,0.005072778,0.001595531,0.02711807],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.99479,"threshold_uncertainty_score":0.03651637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01614647621921824,"score_gpt":0.2159336213629831,"score_spread":0.1997871451437649,"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."}}