{"id":"W4387861647","doi":"10.52842/conf.acadia.2021.048","title":"Automated Generation of Custom Fit PPE Inserts","year":2021,"lang":"en","type":"article","venue":"ACADIA quarterly","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Embedded system","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":[0.0009851514,0.00108811,0.0007427396,0.0009789132,0.0003730475,0.001023463,0.001235216,0.0006360236,0.005222095],"category_scores_gemma":[0.0033119,0.0007566841,0.0009164888,0.0004519288,0.0004068589,0.000730489,0.001256778,0.0005373425,0.001612927],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004605497,"about_ca_system_score_gemma":0.0006280356,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008538536,"about_ca_topic_score_gemma":0.001489389,"domain_scores_codex":[0.9986563,0.0001233434,0.00007292415,0.000245458,0.0008241223,0.00007780137],"domain_scores_gemma":[0.9985202,0.0005655717,0.0001742732,0.0003139657,0.0003813421,0.00004458908],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002509257,0.0002155689,0.003435479,0.000552374,0.00007508694,0.000560027,0.0003791242,0.1970645,0.2428311,0.003800089,0.004831138,0.5460046],"study_design_scores_gemma":[0.00003548732,0.0005368778,0.002527123,0.00003757438,0.00007001439,0.0006564119,0.00009934042,0.8121922,0.1581291,0.00189961,0.02372969,0.00008645722],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0441526,0.0001714519,0.9445236,0.00007512292,0.00007573747,0.0002403136,0.0001658813,0.005765514,0.004829779],"genre_scores_gemma":[0.2450469,0.0001626116,0.7482799,0.00006391092,0.00002422754,0.0001982527,0.0003324375,0.001071283,0.004820446],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005222095,"threshold_uncertainty_score":0.01746958,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01733462509965256,"score_gpt":0.2240908223380561,"score_spread":0.2067561972384036,"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."}}