{"id":"W4400164612","doi":"10.31435/rsglobal_ijitss/30062024/8155","title":"IDENTIFYING COVIDOGENIC ENVIRONMENTS IN URBAN SECTORS OF KHROUB CITY (ALGERIA): A GIS-BASED APPROACH TO ASSESSING PANDEMIC RISK AND VULNERABILITY","year":2024,"lang":"en","type":"article","venue":"International Journal of Innovative Technologies in Social Science","topic":"COVID-19 epidemiological studies","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Agence Universitaire de la Francophonie","keywords":"Vulnerability (computing); Pandemic; Environmental planning; Vulnerability assessment; Environmental resource management; Geography; Scale (ratio); Environmental health; Public health; Coronavirus disease 2019 (COVID-19); Geographic information system; Business; Cartography; Computer science; Medicine; Computer security; Environmental science","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":[0.0005462012,0.0004485714,0.0002551351,0.004399367,0.0008883744,0.001823158,0.0004549031,0.0003978257,0.001680483],"category_scores_gemma":[0.001353291,0.0001948546,0.0002895404,0.003403149,0.0004298745,0.0009025563,0.001485998,0.0002538496,0.000167976],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001449413,"about_ca_system_score_gemma":0.001378572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04682707,"about_ca_topic_score_gemma":0.07073746,"domain_scores_codex":[0.9995772,0.000188986,0.0000372869,0.00005303157,0.00006765063,0.00007577263],"domain_scores_gemma":[0.999368,0.0001763166,0.0001892402,0.00003949168,0.0001642959,0.0000627319],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008724147,0.0001339104,0.8981988,0.0003425686,0.0001283463,0.000847775,0.01207424,0.004641832,0.00192072,0.002154433,0.001601558,0.07786851],"study_design_scores_gemma":[0.000007005041,0.0001078874,0.8652232,0.0002254562,0.00008697293,0.0005188868,0.1075474,0.01572314,0.001113408,0.00188263,0.00751276,0.00005120941],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9865849,0.0003383791,0.004812026,0.0004696191,0.00001053471,0.0001738138,0.001886254,0.00005294094,0.005671529],"genre_scores_gemma":[0.9863565,0.0003948335,0.01154345,0.00004006068,0.000006211898,0.0001133098,0.0008250347,0.000004787624,0.0007157175],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04682707,"threshold_uncertainty_score":0.09310901,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2265923572975839,"score_gpt":0.4754071981522247,"score_spread":0.2488148408546408,"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."}}