{"id":"W2625022492","doi":"10.21433/b3110mb7825q","title":"Spatial Data Considerations for a Trauma Transport Spatial Decision Support System","year":2016,"lang":"en","type":"article","venue":"International Conference on GIScience Short Paper Proceedings","topic":"Traffic and Road Safety","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Context (archaeology); Spatial contextual awareness; Spatial analysis; Operations research; Geographic information system; Computer science; Data science; Geography; Medical emergency; Engineering; Cartography; Medicine; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000404826,0.0002412724,0.0002187976,0.0001490318,0.0001814022,0.0001228391,0.0008493759,0.0001127795,0.0006158124],"category_scores_gemma":[0.0001212093,0.0001728564,0.00007347685,0.00009130613,0.0001583907,0.0009652347,0.00006194726,0.000119623,0.00005713852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001405569,"about_ca_system_score_gemma":0.0001355847,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002585612,"about_ca_topic_score_gemma":0.0002160293,"domain_scores_codex":[0.9978833,0.000003306934,0.000484105,0.0006193918,0.0006616097,0.000348352],"domain_scores_gemma":[0.9990531,0.0001178382,0.00005032456,0.0002507381,0.0003747136,0.0001532603],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004814714,0.0002610024,0.01235175,0.0001659392,0.0002102725,0.00003978984,0.001516565,0.0005964459,0.06306377,0.3419431,0.01446861,0.5649012],"study_design_scores_gemma":[0.005500472,0.001219578,0.1361554,0.002173387,0.0002090725,0.0005123513,0.002049336,0.7112932,0.02183377,0.007848939,0.1080896,0.003114974],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.211263,0.00001484164,0.6228145,0.003193364,0.00527141,0.001528271,0.002012176,0.001350091,0.1525523],"genre_scores_gemma":[0.9957778,0.00001960273,0.003408008,0.000110046,0.0003356858,0.00009093586,0.00004510912,0.00002744432,0.0001853758],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7845147,"threshold_uncertainty_score":0.704888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06110934342906828,"score_gpt":0.2864451514412362,"score_spread":0.225335808012168,"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."}}