{"id":"W3163024691","doi":"10.26389/ajsrp.f060217","title":"Remote sensing and Geographic Information System (GIS) applications in transport geography studies","year":2017,"lang":"en","type":"article","venue":"مجلة العلوم الهندسية و تكنولوجيا المعلومات","topic":"Socioeconomic Development in MENA","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geographic information system; Work (physics); Geography; Scale (ratio); Information system; GIS and public health; Remote sensing; Data science; Environmental planning; Computer science; Environmental resource management; Cartography; Engineering; Environmental science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.002185111,0.0003139076,0.0005174573,0.0005413052,0.002734479,0.000363755,0.0006203173,0.0002562956,0.00001461757],"category_scores_gemma":[0.0002294383,0.0003328178,0.0001389856,0.0003155686,0.0010883,0.001517052,0.0001234149,0.0003031205,0.00006988033],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003003129,"about_ca_system_score_gemma":0.0001771443,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006038549,"about_ca_topic_score_gemma":0.003841388,"domain_scores_codex":[0.997492,0.0001605506,0.0007490034,0.0004633706,0.0004679704,0.0006671269],"domain_scores_gemma":[0.9980417,0.0002362754,0.0005587043,0.0007268495,0.0002250522,0.0002114278],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005048569,0.00004015219,0.7129355,0.0004797399,0.0003422545,0.00002425322,0.06820544,0.00002326925,0.0000216951,0.02374107,0.0003441705,0.193792],"study_design_scores_gemma":[0.001658645,0.00003684781,0.7964821,0.0005227777,0.0001280927,0.00001139323,0.09085865,0.0004335635,0.00004821255,0.007523703,0.1011996,0.001096472],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.933612,0.0009914556,0.002936642,0.002488522,0.001133448,0.001910079,0.00003209508,0.0004528382,0.05644286],"genre_scores_gemma":[0.9938114,0.001314888,0.004171478,0.0002003276,0.0002064425,0.0000359753,0.00002305807,0.00002465166,0.000211825],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1926955,"threshold_uncertainty_score":0.9999124,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02440156124782774,"score_gpt":0.3026553904175727,"score_spread":0.278253829169745,"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."}}