{"id":"W2573050985","doi":"10.1609/socs.v7i1.18385","title":"A Multi-Phase Search Approach to the LEGO Construction Problem","year":2021,"lang":"en","type":"article","venue":"Proceedings of the International Symposium on Combinatorial Search","topic":"BIM and Construction Integration","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Heuristics; Component (thermodynamics); Computer science; Construct (python library); Search problem; Task (project management); Search algorithm; Connected component; Brick; Selection (genetic algorithm); Beam search; Local search (optimization); Phase (matter); Mathematical optimization; Algorithm; Artificial intelligence; Mathematics; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003814138,0.000153984,0.0001433963,0.00008776582,0.0001834208,0.0002051036,0.000676516,0.00009608459,0.00003846665],"category_scores_gemma":[0.00006169485,0.0001081387,0.000115525,0.0005032268,0.0001012082,0.000175102,0.0001744016,0.0004404716,0.00002590597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002238759,"about_ca_system_score_gemma":0.00006813393,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003720151,"about_ca_topic_score_gemma":0.000002936708,"domain_scores_codex":[0.9983416,0.00001978503,0.0003075823,0.0002642701,0.0008451737,0.0002216096],"domain_scores_gemma":[0.9987367,0.00004446745,0.00004764671,0.0001413547,0.0009524523,0.00007732175],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001838957,0.0004839248,0.0009088602,0.0001100736,0.0001965344,5.257352e-7,0.001245948,0.003785068,0.3360141,0.6471147,0.003866068,0.006090302],"study_design_scores_gemma":[0.003574386,0.0002163445,0.0005305423,0.0002142045,0.00004231443,0.0001848966,0.002048329,0.0608728,0.8934836,0.004601321,0.03381538,0.0004158234],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8616078,0.00006447339,0.002120589,0.01058736,0.01244505,0.001230026,0.00006703187,0.0002494783,0.1116282],"genre_scores_gemma":[0.9958252,0.00002495327,0.002887042,0.00007578567,0.0005900714,0.00008928411,0.000008730012,0.00002697215,0.0004719269],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6425133,"threshold_uncertainty_score":0.4409768,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01719473755055864,"score_gpt":0.2538083237308843,"score_spread":0.2366135861803257,"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."}}