{"id":"W4399847219","doi":"10.2139/ssrn.4863710","title":"Community Responder Crowdsourcing for Time-Sensitive Medical Emergencies","year":2024,"lang":"en","type":"preprint","venue":"SSRN Electronic Journal","topic":"Disaster Response and Management","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Crowdsourcing; First responder; Computer science; Data science; Medical emergency; Medicine; World Wide Web","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":[0.003454615,0.0007070276,0.000946327,0.001427023,0.001654114,0.001548271,0.001433932,0.001721418,0.009033267],"category_scores_gemma":[0.01153748,0.0002711032,0.0006528862,0.001425831,0.0004757332,0.001416718,0.003304388,0.001077887,0.003989651],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007955446,"about_ca_system_score_gemma":0.001608455,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009339764,"about_ca_topic_score_gemma":0.01524171,"domain_scores_codex":[0.9974186,0.0009915531,0.00007030912,0.0004408865,0.0008540534,0.0002246277],"domain_scores_gemma":[0.9935417,0.003218008,0.0003339729,0.001390346,0.0009832095,0.0005327996],"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":[0.004613717,0.002639215,0.01735828,0.002426716,0.0008164118,0.001567319,0.00820622,0.07883751,0.06915959,0.01683575,0.1852268,0.6123125],"study_design_scores_gemma":[0.0004564576,0.001064593,0.02841627,0.0002419654,0.0002315255,0.0002840573,0.008695773,0.7922131,0.01171511,0.03338812,0.123068,0.000224975],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6322098,0.001975757,0.2589142,0.006738378,0.003231759,0.003160532,0.008585338,0.01195733,0.07322697],"genre_scores_gemma":[0.9237444,0.0003006497,0.05238743,0.0005271823,0.0005609114,0.0005048668,0.003459827,0.0004490939,0.01806557],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009339764,"threshold_uncertainty_score":0.03021926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05174439551254564,"score_gpt":0.4180560701561383,"score_spread":0.3663116746435927,"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."}}