{"id":"W2883237504","doi":"10.5555/1480-6800.20.4.317","title":"Accounting for Level Decline in the Dead Sea: Land Use and Land Cover Changes, 1984–2015","year":2017,"lang":"en","type":"article","venue":"Arab world geographer","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Normalized Difference Vegetation Index; Thematic Mapper; Physical geography; Land cover; Period (music); Vegetation (pathology); Environmental science; Land use; Geography; Remote sensing; Hydrology (agriculture); Satellite imagery; Geology; Ecology; Climate change; Biology; Oceanography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004052263,0.00009630237,0.00009461066,0.00003580787,0.0004176435,0.0002519099,0.0002236968,0.00003318298,0.00004835724],"category_scores_gemma":[0.00005134133,0.00006749477,0.00003205376,0.0001250761,0.0001611196,0.0001672844,0.0001123096,0.00009112702,0.00004032148],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008951159,"about_ca_system_score_gemma":0.000002888606,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.00708853,"about_ca_topic_score_gemma":0.08446413,"domain_scores_codex":[0.9993099,0.00002333074,0.00009521908,0.0002241026,0.0001340034,0.0002134665],"domain_scores_gemma":[0.9993205,0.0001414073,0.00007835405,0.0004144993,0.000008471088,0.00003673467],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000009307656,0.00002150634,0.9849915,0.000002678266,0.000005394707,0.000001159383,0.0001076002,0.00003220138,0.00006099148,0.00002287492,0.005086394,0.009658396],"study_design_scores_gemma":[0.0003384157,0.000008044618,0.8271899,0.00001030431,0.00001163776,0.00000287083,0.00001044727,0.0006462793,0.00001902565,0.0004666581,0.1712112,0.00008524],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9898726,0.00008287245,0.0001629261,0.005486648,0.00005308379,0.0003430576,0.00002560597,0.00001491615,0.003958292],"genre_scores_gemma":[0.9959121,0.0000397128,0.001434723,0.001134154,0.00006973299,0.0000121659,0.000012022,0.00001049996,0.001374886],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1661248,"threshold_uncertainty_score":0.9995233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03840312620175861,"score_gpt":0.2779624694651577,"score_spread":0.2395593432633991,"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."}}