{"id":"W4394912662","doi":"10.5267/j.ijdns.2024.3.004","title":"Effect of disaster events on regional food security spatially: A geographically weighted regression model","year":2024,"lang":"en","type":"article","venue":"International Journal of Data and Network Science","topic":"Food Security and Health in Diverse Populations","field":"Health Professions","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Geographically Weighted Regression; Geography; Regression; Food security; Regression analysis; Statistics; Mathematics; 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":[0.004176435,0.000986145,0.0008593922,0.001809038,0.0004694748,0.001719696,0.00253704,0.001259569,0.006944115],"category_scores_gemma":[0.009301427,0.000525996,0.002282284,0.002217916,0.0007194843,0.001418172,0.001530281,0.001797713,0.001073775],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001297739,"about_ca_system_score_gemma":0.001202127,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03004603,"about_ca_topic_score_gemma":0.01222809,"domain_scores_codex":[0.9968099,0.001862248,0.0001759953,0.0006415123,0.0002133794,0.0002968945],"domain_scores_gemma":[0.9935759,0.004072951,0.001064083,0.0002676639,0.0007240066,0.0002953316],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000968133,0.0009640013,0.5259178,0.0004771149,0.003197848,0.001810301,0.001596971,0.398356,0.001184236,0.01654974,0.006173681,0.04280414],"study_design_scores_gemma":[0.00009904984,0.0007365735,0.0984566,0.0001226792,0.0009621481,0.0004050097,0.002260242,0.884199,0.0003516696,0.006883787,0.005434828,0.00008837183],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9259266,0.001103962,0.05904926,0.002991886,0.0002497535,0.0004645483,0.003722413,0.0003991006,0.006092493],"genre_scores_gemma":[0.9875633,0.0004366555,0.006640478,0.00008693324,0.0000357705,0.0002264002,0.000978534,0.0000346307,0.003997287],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03004603,"threshold_uncertainty_score":0.05974233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1108414416201839,"score_gpt":0.4730341842532119,"score_spread":0.3621927426330279,"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."}}