{"id":"W2771283930","doi":"10.3390/rs9121323","title":"A New Regionalization Scheme for Effective Ecological Restoration on the Loess Plateau in China","year":2017,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Shrubland; Vegetation (pathology); Grassland; Environmental science; Restoration ecology; Vegetation classification; Loess plateau; Vegetation type; Physical geography; Remote sensing; Geography; Ecology; Ecosystem; Soil science","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":[0.001465133,0.0006317836,0.0004888745,0.002580344,0.001216007,0.00120644,0.0009517623,0.0003478066,0.002739632],"category_scores_gemma":[0.001884648,0.0003665172,0.0006093073,0.00250844,0.000519815,0.001199823,0.00181027,0.0003599799,0.0002733451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001884811,"about_ca_system_score_gemma":0.004451876,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04872755,"about_ca_topic_score_gemma":0.05592787,"domain_scores_codex":[0.9991552,0.0001958364,0.00009029867,0.0002561166,0.0001548818,0.0001478044],"domain_scores_gemma":[0.9992787,0.00005043565,0.00009497573,0.00008266725,0.0003870508,0.0001062191],"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":[0.0004923586,0.0004430125,0.1905165,0.0007173427,0.0001790836,0.0009028815,0.005201512,0.09916904,0.02484463,0.02419334,0.01607064,0.6372696],"study_design_scores_gemma":[0.0004259464,0.001050723,0.367891,0.0001852247,0.0006477923,0.0008260313,0.008387166,0.5090005,0.01159318,0.01128518,0.08834189,0.0003652737],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6508563,0.0008572718,0.3176814,0.0007851996,0.0001205556,0.002861301,0.001758279,0.002487677,0.0225921],"genre_scores_gemma":[0.8054854,0.0002730559,0.186012,0.00005997721,0.00002735048,0.0009840756,0.001828424,0.00008045609,0.005249089],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04872755,"threshold_uncertainty_score":0.09688783,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01673522855138851,"score_gpt":0.2582567899941839,"score_spread":0.2415215614427954,"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."}}