{"id":"W2916979987","doi":"10.5424/fs/2019281-14221","title":"Remote sensing for the Spanish forests in the 21st century: a review of advances, needs, and opportunities","year":2019,"lang":"en","type":"review","venue":"Forest Systems","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":68,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; Canadian Forest Service","funders":"","keywords":"Context (archaeology); Remote sensing; Environmental resource management; Forest ecology; Forest management; Recreation; Ecosystem services; Scale (ratio); Temporal scales; Sustainable forest management; Lidar; Biodiversity; Environmental science; Geography; Ecosystem; Ecology; Agroforestry; Cartography","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":[0.003035042,0.001034914,0.0008631903,0.003646517,0.0003756208,0.002093478,0.001043702,0.001454032,0.002250354],"category_scores_gemma":[0.00269722,0.000324327,0.0007586292,0.004152827,0.001231405,0.002736872,0.0008539244,0.001595186,0.0009328271],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001654284,"about_ca_system_score_gemma":0.00240816,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008098383,"about_ca_topic_score_gemma":0.006283208,"domain_scores_codex":[0.9990127,0.0002058311,0.0001098755,0.0001870713,0.0004210538,0.00006327857],"domain_scores_gemma":[0.9972234,0.001372367,0.0002135273,0.0000960797,0.0009918809,0.0001028265],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003576001,0.00003704549,0.001475746,0.009333994,0.00008482613,0.000169168,0.000315044,0.0007324365,0.001479598,0.009267872,0.02596928,0.9510992],"study_design_scores_gemma":[0.00000423559,0.00004596706,0.004910945,0.006465956,0.00008388746,0.0006508887,0.0004131378,0.0002937806,0.0002672006,0.004672186,0.9821536,0.00003812097],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0003785961,0.9953086,0.0007973238,0.001141932,0.0004626522,0.000009143672,0.00004971891,0.00001167657,0.001840331],"genre_scores_gemma":[0.004208978,0.9906809,0.002267079,0.0007078581,0.001032457,0.00001269138,0.0001353971,0.00001612194,0.000938653],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.008098383,"threshold_uncertainty_score":0.01610249,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.066080302267149,"score_gpt":0.3043018267396413,"score_spread":0.2382215244724923,"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."}}