{"id":"W2051814330","doi":"10.1017/cem.2014.54","title":"Crowdsourcing: an instructional method at an emergency medicine continuing education course","year":2015,"lang":"en","type":"article","venue":"Canadian Journal of Emergency Medicine","topic":"Knowledge Management and Sharing","field":"Social Sciences","cited_by":10,"is_retracted":false,"has_abstract":false,"ca_institutions":"Schwartz/Reisman Emergency Medicine Institute; University of Toronto","funders":"","keywords":"Medicine; Course (navigation); Crowdsourcing; Content (measure theory); Continuing education; Action (physics); Medical education; Online course; World Wide Web; Computer science; 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":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.004581786,0.0001954729,0.0003822056,0.0005644578,0.0005422871,0.00001074687,0.0005901376,0.0001101775,0.01726507],"category_scores_gemma":[0.001753766,0.0001707896,0.00007867066,0.0007360146,0.0002557132,0.0007850804,0.0000196494,0.0002736413,0.00001612328],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004573508,"about_ca_system_score_gemma":0.001553096,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.03582922,"about_ca_topic_score_gemma":0.2854959,"domain_scores_codex":[0.9971,0.0004342736,0.001006135,0.0002462504,0.0007240804,0.0004892624],"domain_scores_gemma":[0.9950197,0.00003003957,0.0006036841,0.0002440027,0.001503331,0.002599278],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000603023,0.0001181399,0.1963576,0.00004394416,0.0001386408,0.00003779291,0.169699,0.00009354432,0.0003917539,0.03036749,0.5141273,0.08856447],"study_design_scores_gemma":[0.0009220961,0.0006262625,0.01948038,0.0002550395,0.0002764839,0.00001770733,0.1040627,0.0002158352,0.000008339956,0.007898346,0.8659081,0.0003286582],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6777204,0.008114652,0.00184217,0.01127036,0.07242236,0.000356385,0.000004647177,0.00004113358,0.2282279],"genre_scores_gemma":[0.9424009,0.0005556316,0.001193989,0.0001317648,0.02143961,0.00000672133,0.00003732735,0.00004490763,0.03418912],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3517808,"threshold_uncertainty_score":0.9836333,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1676600490760488,"score_gpt":0.4406209198305781,"score_spread":0.2729608707545292,"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."}}