{"id":"W2620642391","doi":"","title":"USING SATELLITE IMAGERY TO ESTIMATE THE RATE OF VEGETATION COVER IN THE WATERSHED OF CHOTT CHERGUI -WILAYA OF EL BAYADH (HIGH STEPPE PLAINS OF ALGERIA)","year":2014,"lang":"en","type":"article","venue":"The Journal of Internet Banking and Commerce","topic":"Water management and technologies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Vegetation (pathology); Normalized Difference Vegetation Index; Watershed; Hydrology (agriculture); Erosion; Satellite imagery; Physical geography; Enhanced vegetation index; Vegetation cover; Environmental science; Plant cover; Shrub; Geography; Remote sensing; Forestry; Vegetation Index; Geology; Grazing; Ecology; Geomorphology; Climate change; Archaeology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.0001490294,0.0001782637,0.0001159396,0.001386795,0.0001273899,0.0003010328,0.0001450599,0.0001848154,0.0003961405],"category_scores_gemma":[0.0002512699,0.00007881781,0.0001448327,0.001126763,0.0001018491,0.000223352,0.0001377133,0.0001036426,0.00009806143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003321505,"about_ca_system_score_gemma":0.0002459252,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03716992,"about_ca_topic_score_gemma":0.05894769,"domain_scores_codex":[0.9999262,0.000007537641,0.000006575081,0.00001743976,0.00002548538,0.00001678282],"domain_scores_gemma":[0.9998907,0.00001605797,0.00003284597,0.000007717743,0.0000398015,0.00001282752],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001727839,0.0002498639,0.913386,0.0001127534,0.0001150989,0.0003708239,0.0007360303,0.009527775,0.02275787,0.0001272143,0.0007148929,0.05172884],"study_design_scores_gemma":[0.000007152122,0.00003265488,0.9765241,0.000008115018,0.00002191908,0.00008755081,0.000520294,0.02031006,0.002019424,0.00002947819,0.0004330334,0.000006307422],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985393,0.00002989268,0.000383821,0.00001082608,0.000001091513,0.00001096285,0.0006553466,0.00002434465,0.000344363],"genre_scores_gemma":[0.9947247,0.0000569643,0.003115799,0.000006372004,0.000002461685,0.0000164695,0.001719849,0.000003342302,0.0003541055],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03716992,"threshold_uncertainty_score":0.07390714,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02744726125335357,"score_gpt":0.2670516731535109,"score_spread":0.2396044119001573,"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."}}