{"id":"W4210497080","doi":"10.1161/str.53.suppl_1.tmp32","title":"Abstract TMP32: Modeling Optimal Patient Transport In A Stroke Network Capable Of Telerobotic Endovascular Therapy","year":2022,"lang":"en","type":"article","venue":"Stroke","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University; University of Calgary","funders":"","keywords":"Medicine; Catchment area; Robotics; Stroke (engine); Population; Robot; Artificial intelligence; Computer science; Drainage basin; Geography; Cartography; Engineering","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":[0.001348595,0.00157664,0.0009114493,0.001011559,0.0008859974,0.001895647,0.00188108,0.003089884,0.007787949],"category_scores_gemma":[0.003644653,0.001347602,0.001587719,0.0008708087,0.001354814,0.001068069,0.001559494,0.001592204,0.0005514696],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003932814,"about_ca_system_score_gemma":0.003424219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1554203,"about_ca_topic_score_gemma":0.0516523,"domain_scores_codex":[0.9994432,0.0001910738,0.0000175024,0.0001547089,0.00002972134,0.0001637895],"domain_scores_gemma":[0.9980037,0.001194581,0.0002329272,0.00005260844,0.0002609623,0.0002553425],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0000283757,0.00001684964,0.001081907,0.000006916608,0.000006433935,0.00002731453,0.000008895638,0.9979004,0.0000334661,0.0003827997,0.0001898555,0.0003169434],"study_design_scores_gemma":[0.00001606385,0.00001774101,0.0003544005,0.000003640986,0.000004831491,0.000006368525,0.00002269279,0.9991471,0.00001721343,0.0003170912,0.00008952332,0.000003298092],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9159601,0.0003499199,0.06171661,0.002235462,0.0001342756,0.0002806403,0.00574047,0.0004688938,0.0131136],"genre_scores_gemma":[0.9839265,0.0001268808,0.008558047,0.000103816,0.0000284716,0.0001858877,0.001319551,0.0000448897,0.005706005],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1554203,"threshold_uncertainty_score":0.3090312,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0155620410182294,"score_gpt":0.2077002504196916,"score_spread":0.1921382094014622,"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."}}