{"id":"W3013279890","doi":"10.3390/ijerph17072238","title":"The Natural Environmental Factors Influencing the Spatial Distribution of Marathon Event: A Case Study from China","year":2020,"lang":"en","type":"article","venue":"International Journal of Environmental Research and Public Health","topic":"Advanced Technologies in Various Fields","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Health Services","funders":"","keywords":"Buffer zone; Plateau (mathematics); Landform; Subtropics; Monsoon; Physical geography; Temperate climate; Climate change; Environmental science; Terrain; Drainage basin; Hydrology (agriculture); Climatology; Geography; Geology; Ecology; Oceanography; Cartography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.0007182587,0.000576943,0.000364173,0.00209449,0.001968795,0.00089855,0.001085575,0.0004971088,0.001559891],"category_scores_gemma":[0.001342673,0.000280635,0.0006086082,0.003615699,0.0008270781,0.0005888537,0.001217726,0.0004677554,0.0001194833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003305301,"about_ca_system_score_gemma":0.00305179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2153005,"about_ca_topic_score_gemma":0.2624443,"domain_scores_codex":[0.9992705,0.0001559659,0.00005284055,0.000121625,0.0001538953,0.0002450886],"domain_scores_gemma":[0.999022,0.0001482808,0.0002721786,0.00006991357,0.0001764333,0.000311291],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005549475,0.0001224354,0.9760733,0.00008372764,0.00006753998,0.009014942,0.005019832,0.001095266,0.0004560416,0.0002604652,0.0006210173,0.00712995],"study_design_scores_gemma":[0.00001088457,0.00009651093,0.9762066,0.00004607369,0.00006212931,0.001649125,0.01689093,0.003347344,0.000219734,0.0001383735,0.001305555,0.00002659384],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990614,0.00007314442,0.0001357995,0.00009658525,0.000002783097,0.0000199557,0.000134395,0.000004656723,0.0004712667],"genre_scores_gemma":[0.9990261,0.0001764628,0.0002286405,0.00002331646,0.00000546413,0.00001790569,0.0001873122,0.000002345445,0.0003323392],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2153005,"threshold_uncertainty_score":0.4280947,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03871374277123497,"score_gpt":0.3452967385245695,"score_spread":0.3065829957533345,"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."}}