{"id":"W2032851458","doi":"10.1111/j.1467-9671.2006.01016.x","title":"Map-Based Exploratory Evaluation of Non-Medical Determinants of Population Health","year":2006,"lang":"en","type":"article","venue":"Transactions in GIS","topic":"Geographic Information Systems Studies","field":"Social Sciences","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Analytic hierarchy process; Visualization; Geographic information system; Computer science; Exploratory research; Decision support system; Population; Space (punctuation); Creative visualization; Decision analysis; Operations research; Management science; Data mining; Geography; Cartography; Engineering; Mathematics; Statistics; Medicine; Environmental health","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01055529,0.0008579746,0.0006431828,0.004799846,0.00066977,0.002394823,0.0007533525,0.0004436957,0.002380476],"category_scores_gemma":[0.04173858,0.0002472022,0.0006147801,0.003794995,0.0006651325,0.001425857,0.001766165,0.0004055722,0.0001947188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001042136,"about_ca_system_score_gemma":0.001648987,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006939495,"about_ca_topic_score_gemma":0.01176571,"domain_scores_codex":[0.986775,0.01073323,0.0002664549,0.0002002226,0.001903931,0.0001211605],"domain_scores_gemma":[0.9429583,0.04959742,0.001705152,0.001774966,0.003508659,0.0004555032],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.002221473,0.000842299,0.1215693,0.002318521,0.001067284,0.000837446,0.01566988,0.1095847,0.008576048,0.02799044,0.006483005,0.7028397],"study_design_scores_gemma":[0.0003856186,0.002447931,0.2275469,0.0008948189,0.0005614454,0.001024015,0.01701445,0.6567318,0.02054382,0.05121458,0.02119859,0.0004360082],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6222622,0.001127883,0.3411235,0.001146046,0.00005408375,0.001450428,0.002528051,0.002277334,0.02803049],"genre_scores_gemma":[0.8759186,0.0002950135,0.1225375,0.00003003413,0.00001182942,0.0004018495,0.0003474568,0.00004357036,0.0004140876],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01055529,"threshold_uncertainty_score":0.05582243,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04261580469423414,"score_gpt":0.3676837760786393,"score_spread":0.3250679713844052,"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."}}