{"id":"W2757035646","doi":"10.3390/geosciences7040094","title":"Using Open Access Satellite Data Alongside Ground Based Remote Sensing: An Assessment, with Case Studies from Egypt’s Delta","year":2017,"lang":"en","type":"article","venue":"Geosciences","topic":"Archaeological Research and Protection","field":"Earth and Planetary Sciences","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Social Sciences and Humanities Research Council of Canada; National Geographic Society; National Science Foundation","keywords":"Delta; Remote sensing; Nile delta; Threatened species; Satellite; Urbanization; Geography; Groundwater; Environmental science; Earth science; Geology; Water resource management; Engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0019447,0.0004057594,0.0001992399,0.001987479,0.0006423233,0.001280159,0.0004414042,0.0007955195,0.0007412625],"category_scores_gemma":[0.002584326,0.0001595646,0.0003431637,0.003242286,0.0007055028,0.0009494554,0.0008956178,0.0002650374,0.0001333282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001557339,"about_ca_system_score_gemma":0.0006243238,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0337089,"about_ca_topic_score_gemma":0.06869446,"domain_scores_codex":[0.9990464,0.0005136304,0.00004741798,0.00006480787,0.0002088539,0.000118909],"domain_scores_gemma":[0.9977899,0.001216153,0.0002458098,0.0001347113,0.0005141452,0.00009916198],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009203406,0.001362936,0.7743445,0.0007935535,0.0002163914,0.02165272,0.006715585,0.01611127,0.005893492,0.002871672,0.001477465,0.16764],"study_design_scores_gemma":[0.0001548856,0.002659785,0.8408764,0.0006014796,0.0006141767,0.00775618,0.07563759,0.04382342,0.008741345,0.002319043,0.01668059,0.0001351695],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9963428,0.000445924,0.0005786463,0.0001711445,0.000004343748,0.00003804211,0.00009872248,0.000005339672,0.002314904],"genre_scores_gemma":[0.9956385,0.001225104,0.002234983,0.00004198025,0.000009254487,0.00001527907,0.0001684289,0.000004156774,0.0006623226],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0337089,"threshold_uncertainty_score":0.06702536,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5194671361475154,"score_gpt":0.514334070612042,"score_spread":0.005133065535473436,"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."}}