{"id":"W4294891725","doi":"10.1145/3533387","title":"Dissecting My Data Body","year":2022,"lang":"en","type":"article","venue":"Proceedings of the ACM on Computer Graphics and Interactive Techniques","topic":"Empathy and Medical Education","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"The arts; Virtual reality; Data science; Social media; Big data; Computer science; Internet privacy; Sociology; Engineering ethics; World Wide Web; Human–computer interaction; Engineering; Visual arts; Art","routes":{"ca_aff":true,"ca_fund":true,"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":[0.03972621,0.0006342693,0.0006048451,0.003371043,0.01474842,0.02888721,0.00334403,0.007114002,0.009943917],"category_scores_gemma":[0.08677272,0.0006933477,0.0007083552,0.002397911,0.06004395,0.02721499,0.02122353,0.01358209,0.003706006],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007449776,"about_ca_system_score_gemma":0.01106022,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003605985,"about_ca_topic_score_gemma":0.003066282,"domain_scores_codex":[0.954733,0.03070657,0.001147503,0.003824431,0.00757664,0.002011891],"domain_scores_gemma":[0.937695,0.03812559,0.002998971,0.007080475,0.009625351,0.004474642],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000207107,0.00001562548,0.0004169691,0.00009800942,0.00000596615,0.0002612249,0.116598,0.0001144937,0.0002577748,0.8048347,0.05976885,0.01760758],"study_design_scores_gemma":[0.000008494868,0.00001585679,0.0001647732,0.0005602724,0.000004691155,0.0003522874,0.07569902,0.0003173634,0.0002942932,0.167667,0.7548935,0.00002244934],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.02104917,0.004729525,0.0680109,0.7225665,0.009921271,0.0001513141,0.0003201955,0.0002782729,0.1729728],"genre_scores_gemma":[0.5693244,0.008423968,0.06107524,0.1984209,0.009112756,0.001136205,0.0007143947,0.001758751,0.1500335],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03972621,"threshold_uncertainty_score":0.2100948,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03522986588336567,"score_gpt":0.3324493206405801,"score_spread":0.2972194547572145,"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."}}