{"id":"W2986862432","doi":"10.1145/3359131","title":"Makers and Quilters","year":2019,"lang":"en","type":"article","venue":"Proceedings of the ACM on Human-Computer Interaction","topic":"Biomedical and Engineering Education","field":"Engineering","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Ontario Ministry of Research, Innovation and Science; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Diversification (marketing strategy); Inclusion (mineral); Context (archaeology); Space (punctuation); Sociology; Psychology; Knowledge management; Social psychology; Marketing; Business; Computer science; Geography","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":[0.003325415,0.0006518476,0.0003319128,0.001602659,0.002930089,0.008519907,0.000896624,0.001358627,0.03969737],"category_scores_gemma":[0.01149844,0.0003400533,0.0003209246,0.0009234643,0.002573468,0.004375709,0.00544603,0.00100672,0.005597651],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008535344,"about_ca_system_score_gemma":0.000903926,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005203484,"about_ca_topic_score_gemma":0.0014296,"domain_scores_codex":[0.9969131,0.001425736,0.0001559084,0.0004524334,0.0007174693,0.0003354063],"domain_scores_gemma":[0.9959127,0.002005635,0.0004126108,0.0004924183,0.0003410685,0.0008355128],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.000757416,0.0007142387,0.02945041,0.001130864,0.00005409081,0.001776075,0.1457657,0.0007225687,0.01190826,0.278217,0.06038477,0.4691185],"study_design_scores_gemma":[0.00006341586,0.0003567753,0.00849372,0.0003290183,0.00003039252,0.0008113886,0.03805375,0.0005750137,0.003641277,0.03701089,0.9105865,0.00004780074],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.4144852,0.003057601,0.04652833,0.009711421,0.001599481,0.000800637,0.0007469807,0.001605875,0.5214645],"genre_scores_gemma":[0.7395247,0.001113291,0.02273422,0.002656162,0.0002351619,0.0003409605,0.0004807506,0.0003371183,0.2325778],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03969737,"threshold_uncertainty_score":0.1328009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01689255924796108,"score_gpt":0.2485310042368412,"score_spread":0.2316384449888801,"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."}}