{"id":"W4410240055","doi":"10.3390/make7020042","title":"Leveraging Failure Modes and Effect Analysis for Technical Language Processing","year":2025,"lang":"en","type":"article","venue":"Machine Learning and Knowledge Extraction","topic":"Topic Modeling","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydro-Québec; Université du Québec à Trois-Rivières","funders":"Natural Sciences and Engineering Research Council of Canada; Hydro-Québec; Université du Québec à Trois-Rivières","keywords":"Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005150762,0.0001061202,0.0001729069,0.0002653193,0.0003121675,0.0001951229,0.00009019767,0.00006574894,0.000001278009],"category_scores_gemma":[0.0001374182,0.00009400565,0.00004962176,0.0003843916,0.00001627521,0.0002122312,0.00008804683,0.0002591317,6.319884e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002635102,"about_ca_system_score_gemma":0.0000202667,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003798946,"about_ca_topic_score_gemma":0.00006391283,"domain_scores_codex":[0.9992459,0.00008588852,0.0001312078,0.0003432214,0.00005501314,0.0001386999],"domain_scores_gemma":[0.9995517,0.0002210119,0.00005093686,0.0001078418,0.00003519624,0.00003337291],"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":[0.00001788971,0.00002765716,0.04463736,0.0002458006,0.00007141961,0.00000187659,0.001084127,0.00280458,0.00830956,0.001333295,0.00002041744,0.941446],"study_design_scores_gemma":[0.0003221617,0.00003408606,0.004819503,0.0000481986,0.0000972585,0.000008062779,0.0000938914,0.9921177,0.0004674852,0.0001390816,0.001755853,0.00009669198],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1099155,0.003366383,0.8846742,0.0003087297,0.00003378825,0.0001038105,2.21801e-7,0.0001931176,0.001404265],"genre_scores_gemma":[0.979076,0.00001321436,0.01972808,0.00001362674,0.00004391602,0.00002100067,0.000004074049,0.000005221885,0.001094813],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9893131,"threshold_uncertainty_score":0.3833439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008437007984600979,"score_gpt":0.3089078859271225,"score_spread":0.3004708779425216,"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."}}