{"id":"W4408963024","doi":"10.61091/jcmcc125-26","title":"Research on balancing strategies between modularization and personalization in prefabricated building design and simulation","year":2025,"lang":"en","type":"article","venue":"Journal of Combinatorial Mathematics and Combinatorial Computing","topic":"BIM and Construction Integration","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Modular programming; Personalization; Architectural engineering; Computer science; Mass customization; Engineering; Systems engineering; World Wide Web; Programming language","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009206986,0.0006642945,0.0004576125,0.0007616582,0.0005913356,0.001123439,0.0007935136,0.0005466804,0.004316083],"category_scores_gemma":[0.002213167,0.0003257059,0.0007973877,0.0006664304,0.0006207044,0.001787239,0.000945233,0.0005396295,0.000321382],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008431724,"about_ca_system_score_gemma":0.0008966594,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00353449,"about_ca_topic_score_gemma":0.003096323,"domain_scores_codex":[0.9993661,0.0002377119,0.00002893089,0.000115539,0.0001819657,0.00006982309],"domain_scores_gemma":[0.9994946,0.0002154689,0.00005443623,0.00007004917,0.0001132754,0.00005215372],"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":[0.00007560791,0.0001365484,0.006180338,0.0002599356,0.00007361484,0.00008341082,0.0006859254,0.7613454,0.007891756,0.0624382,0.001295965,0.1595333],"study_design_scores_gemma":[0.00002052375,0.0001019322,0.001499222,0.00003614391,0.00004401346,0.00005374436,0.0002167981,0.9729677,0.00251418,0.01606174,0.006463408,0.00002070819],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1117094,0.001246657,0.8590071,0.000431419,0.00006793548,0.000116624,0.00003969991,0.0003037288,0.0270775],"genre_scores_gemma":[0.8708174,0.001388849,0.1217687,0.00006923256,0.00003477429,0.0001663776,0.00008088772,0.00007090282,0.00560298],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004316083,"threshold_uncertainty_score":0.01443875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02725382913677415,"score_gpt":0.3052174338250521,"score_spread":0.2779636046882779,"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."}}