{"id":"W4406916423","doi":"10.1080/0305215x.2025.2450686","title":"Effective prompting with ChatGPT for problem formulation in engineering optimization","year":2025,"lang":"en","type":"article","venue":"Engineering Optimization","topic":"Software Reliability and Analysis Research","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematical optimization; Engineering optimization; Multidisciplinary design optimization; Computer science; Optimization problem; Mathematics; Multidisciplinary approach","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":[0.009893957,0.00188,0.00114281,0.0007301369,0.0005172254,0.00162284,0.002240379,0.001640824,0.01404888],"category_scores_gemma":[0.09351077,0.0004911272,0.000582027,0.0006306004,0.001012587,0.002883821,0.002471727,0.002258949,0.003533414],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000790523,"about_ca_system_score_gemma":0.001017117,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000405591,"about_ca_topic_score_gemma":0.0006181929,"domain_scores_codex":[0.9916285,0.006085848,0.0004513023,0.0007739731,0.000880676,0.000179609],"domain_scores_gemma":[0.8711299,0.113616,0.003559141,0.006434693,0.004230996,0.001029251],"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":[0.004335588,0.002689726,0.007493793,0.005370576,0.0001256725,0.001357101,0.01483208,0.08074706,0.06731053,0.02091892,0.01839644,0.7764226],"study_design_scores_gemma":[0.001419016,0.007117687,0.01271663,0.002008677,0.0002190722,0.001553876,0.005724073,0.7361431,0.0710207,0.0903375,0.07131805,0.0004215568],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1037415,0.0002683475,0.8764821,0.0007233708,0.0002382948,0.001538941,0.0002961836,0.008034273,0.008676878],"genre_scores_gemma":[0.3860243,0.0003401201,0.6042223,0.0004733352,0.0001343791,0.002225245,0.0005426442,0.0008683627,0.005169335],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01404888,"threshold_uncertainty_score":0.05232483,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003762064502559939,"score_gpt":0.2247621972768631,"score_spread":0.2210001327743032,"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."}}