{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003141042,0.00007571488,0.0000967263,0.00004342027,0.00002375608,0.00002457632,0.00005045687,0.00007566596,0.0001199458],"category_scores_gemma":[0.000005342607,0.00008049687,0.00002459902,0.0001099589,0.000006776691,0.0001359621,0.000002927164,0.00005839006,0.0000258323],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001576894,"about_ca_system_score_gemma":0.00001737237,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001218383,"about_ca_topic_score_gemma":0.00002306988,"domain_scores_codex":[0.9995463,0.00001076403,0.0001605925,0.00009590451,0.00007963539,0.000106795],"domain_scores_gemma":[0.9997607,0.000009565208,0.0000243807,0.0001228293,0.00004792718,0.00003455068],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008799178,0.00008194638,0.0007044374,0.000557802,0.0001343357,0.00003305119,0.006419843,0.7766871,0.0675481,0.001051035,0.0213035,0.12547],"study_design_scores_gemma":[0.0002321823,0.00004930106,0.003718173,0.00002460646,0.00001488262,0.000005783298,0.00005972097,0.864185,0.1278323,0.00007020134,0.003648056,0.000159812],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9906445,0.0003633514,0.0062553,0.00006527894,0.0003337169,0.00005961642,0.000007535427,0.000545175,0.00172554],"genre_scores_gemma":[0.9981316,0.0000351495,0.001491015,0.00003442161,0.0000717475,0.00000687424,0.00005241654,0.00001658968,0.0001601313],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1253102,"threshold_uncertainty_score":0.3282567,"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."}}