{"id":"W2391995667","doi":"","title":"Change of Vegetation Coverage in the Qilian Mountains in Recent 10 Years","year":2014,"lang":"en","type":"article","venue":"Arid Zone Research","topic":"Remote Sensing and Land Use","field":"Earth and Planetary Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Science North","funders":"","keywords":"Vegetation (pathology); Normalized Difference Vegetation Index; Precipitation; Environmental science; Physical geography; Climate change; Growing season; Climatology; Period (music); Spatial change; Enhanced vegetation index; Geography; Vegetation Index; Geology; Ecology; Meteorology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00233412,0.00004181771,0.00008399372,0.000177325,0.00003996873,0.00002828255,0.0001515603,0.00003939298,0.000155408],"category_scores_gemma":[0.0001847227,0.00002858555,0.00001426497,0.0004991061,0.00005608737,0.00007312142,0.00000759168,0.0002236811,0.0001418108],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006650605,"about_ca_system_score_gemma":0.00003480637,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01707745,"about_ca_topic_score_gemma":0.05812643,"domain_scores_codex":[0.9986197,0.0005020416,0.0001224078,0.0001230958,0.0003872298,0.0002455675],"domain_scores_gemma":[0.9993135,0.0004277778,0.00001966218,0.0001705073,0.00003563498,0.00003296412],"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":[0.0000830869,0.00004831652,0.238024,0.00003702551,0.000002960209,0.00002625727,0.004450105,0.0006857694,0.00007035449,0.00008920173,0.0002988229,0.7561841],"study_design_scores_gemma":[0.0002385188,0.000131723,0.9722327,0.00003574489,6.120637e-7,0.000001572759,0.0002093418,0.009384499,0.0000483459,0.0004133718,0.01726449,0.0000390528],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9878921,0.000287791,0.00000553716,0.0008887715,0.00004569397,0.0001518344,0.000002874758,0.000003616241,0.01072179],"genre_scores_gemma":[0.9987816,0.000913044,0.00003254225,0.00008907366,0.00006644056,4.533424e-7,0.00002539763,0.000001680418,0.00008973715],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7561451,"threshold_uncertainty_score":0.9894679,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08886069139883504,"score_gpt":0.3226260988978341,"score_spread":0.233765407498999,"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."}}