{"id":"W2115286752","doi":"10.1145/2638728.2641716","title":"Recording events, interactions, and annotations to communicate reasoning in medical situations","year":2014,"lang":"en","type":"article","venue":"","topic":"Context-Aware Activity Recognition Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Process (computing); Context (archaeology); Reliability (semiconductor); Data collection; Human–computer interaction; Order (exchange); Data science","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":[0.003838685,0.001084709,0.000523574,0.002349379,0.0008922172,0.002684595,0.001074349,0.001247362,0.003612416],"category_scores_gemma":[0.02251594,0.0004097787,0.0003603189,0.001657617,0.001062145,0.00376453,0.002171208,0.001150903,0.0012544],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003776142,"about_ca_system_score_gemma":0.0008698621,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00192059,"about_ca_topic_score_gemma":0.003659831,"domain_scores_codex":[0.9955955,0.002511425,0.0003815524,0.0006434514,0.0006833018,0.0001847504],"domain_scores_gemma":[0.9796578,0.0137836,0.001526788,0.002928445,0.001447943,0.0006554509],"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":[0.002085528,0.0006802148,0.03404017,0.002715592,0.0002152565,0.001186201,0.04028754,0.006226612,0.1045364,0.01080012,0.008895543,0.7883309],"study_design_scores_gemma":[0.0006218764,0.003042144,0.1952998,0.003222818,0.001107866,0.005621777,0.05115403,0.1787266,0.2096712,0.1004386,0.249829,0.001264194],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1724215,0.00200423,0.7908301,0.001931986,0.0003841499,0.001513325,0.003322089,0.0079741,0.01961856],"genre_scores_gemma":[0.5624369,0.0009507228,0.4297815,0.0003994473,0.0002361887,0.0006966038,0.00173952,0.0004365884,0.003322578],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003838685,"threshold_uncertainty_score":0.02030116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0288526575367859,"score_gpt":0.3145374078944112,"score_spread":0.2856847503576253,"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."}}