{"id":"W4402330701","doi":"10.1002/iis2.13185","title":"Providing tailored heuristic advice to Systems Engineers","year":2024,"lang":"en","type":"article","venue":"INCOSE International Symposium","topic":"Systems Engineering Methodologies and Applications","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lockheed Martin (Canada)","funders":"","keywords":"Heuristics; Computer science; Heuristic; Set (abstract data type); Advice (programming); Prioritization; Task (project management); Heuristic evaluation; Meaning (existential); Test (biology); Machine learning; Artificial intelligence; Management science; Usability; Human–computer interaction; Psychology; Engineering; Systems engineering","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":[0.01441697,0.001159175,0.0005902267,0.002383657,0.0008767655,0.003105407,0.0013273,0.001344228,0.005248071],"category_scores_gemma":[0.1170167,0.0005176513,0.0003863204,0.0009172925,0.0005972693,0.002601094,0.00202493,0.001200362,0.001443424],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001227737,"about_ca_system_score_gemma":0.001695684,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009919688,"about_ca_topic_score_gemma":0.002619502,"domain_scores_codex":[0.9848784,0.009826622,0.001044892,0.0009153344,0.00284688,0.0004878413],"domain_scores_gemma":[0.8409206,0.1261944,0.008241985,0.01047514,0.01200726,0.002160458],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008571373,0.002347449,0.04916279,0.00199753,0.0001156332,0.0008593074,0.03067563,0.01615456,0.02526683,0.00529662,0.02349546,0.843771],"study_design_scores_gemma":[0.001310501,0.008345798,0.1045165,0.006913221,0.0007544392,0.003135258,0.05888433,0.3484449,0.09551568,0.07240378,0.2986353,0.001140295],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.7398604,0.0005056162,0.2181316,0.003779957,0.00014634,0.00143034,0.0004791495,0.008885163,0.02678158],"genre_scores_gemma":[0.6908782,0.0002668124,0.3034332,0.0005275691,0.00004494806,0.0003858499,0.0004131522,0.0004125923,0.003637827],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01441697,"threshold_uncertainty_score":0.07624519,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01526364521971184,"score_gpt":0.2623283989811357,"score_spread":0.2470647537614239,"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."}}