{"id":"W4400108501","doi":"10.1016/j.aei.2024.102649","title":"Optimization to identify the adapted product design and product adaptation process with initial evaluation of information quality in branches of AND-OR tree based on information entropy","year":2024,"lang":"en","type":"article","venue":"Advanced Engineering Informatics","topic":"Product Development and Customization","field":"Business, Management and Accounting","cited_by":7,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"","keywords":"Computer science; Product (mathematics); Entropy (arrow of time); Adaptation (eye); Process (computing); Tree (set theory); Data mining; Mathematics; Biology","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":[0.00134481,0.0009842432,0.0009364765,0.001455687,0.000532068,0.001172529,0.0006103686,0.000640303,0.00236261],"category_scores_gemma":[0.003412312,0.0003381233,0.001008693,0.001091871,0.0004272217,0.00141967,0.0006157274,0.000547923,0.0002835909],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008277518,"about_ca_system_score_gemma":0.001831223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005097762,"about_ca_topic_score_gemma":0.002692499,"domain_scores_codex":[0.9990079,0.0002700641,0.00006547017,0.0002098617,0.0003180479,0.0001286734],"domain_scores_gemma":[0.998711,0.0006247154,0.0001445391,0.00009987889,0.0003851849,0.00003478194],"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":[0.0003771358,0.0003156124,0.007838726,0.0003830352,0.0001315658,0.000121352,0.000218378,0.7117548,0.02622081,0.009311688,0.001227632,0.2420993],"study_design_scores_gemma":[0.000009314191,0.00009553289,0.00145897,0.000009117172,0.00003520624,0.00001575685,0.00002872932,0.9921022,0.004394083,0.001557461,0.0002843598,0.000009237213],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.130669,0.000268332,0.8644688,0.00008924339,0.00002096536,0.0001553778,0.0001094981,0.0007262502,0.003492493],"genre_scores_gemma":[0.7961021,0.0001488059,0.201744,0.00003617201,0.000009696823,0.0002064144,0.0003654829,0.00009796527,0.001289486],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005097762,"threshold_uncertainty_score":0.01013619,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0257965863878307,"score_gpt":0.2762647558418487,"score_spread":0.250468169454018,"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."}}