{"id":"W2168057526","doi":"10.1017/s0890060403172034","title":"A feature ontology to support construction cost estimating","year":2003,"lang":"en","type":"article","venue":"Artificial intelligence for engineering design analysis and manufacturing","topic":"BIM and Construction Integration","field":"Engineering","cited_by":59,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"University of British Columbia","keywords":"Computer science; Ontology; Feature (linguistics); Component (thermodynamics); Estimator; Product (mathematics); Similarity (geometry); Data mining; Artificial intelligence; Mathematics; Statistics","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":[0.003083651,0.0007778721,0.0007641187,0.003641178,0.001265649,0.003927415,0.003080273,0.001672629,0.004034784],"category_scores_gemma":[0.01056643,0.001211669,0.00245722,0.003913595,0.001367048,0.008589131,0.002867962,0.002631399,0.001113189],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003012846,"about_ca_system_score_gemma":0.004821352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01853742,"about_ca_topic_score_gemma":0.02538028,"domain_scores_codex":[0.9970246,0.0004737618,0.0005256463,0.0004453879,0.001357683,0.0001728391],"domain_scores_gemma":[0.9958256,0.001336251,0.0004233861,0.001353043,0.0009088308,0.000152833],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00006801575,0.0002347077,0.003758134,0.0004370068,0.00009625076,0.0004454042,0.001270082,0.07837096,0.004665424,0.6781944,0.01867262,0.2137871],"study_design_scores_gemma":[0.00004679283,0.00005990535,0.001750354,0.0004077614,0.0001120429,0.0007562214,0.0005905611,0.4456436,0.007325915,0.2180935,0.3250922,0.0001211954],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003389812,0.00007033646,0.9869401,0.0003469272,0.00003167146,0.0001991361,0.001633625,0.002785864,0.00460252],"genre_scores_gemma":[0.04697679,0.000238004,0.9456157,0.0001257302,0.00002123284,0.0004014101,0.004336008,0.0005322563,0.001752905],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01853742,"threshold_uncertainty_score":0.03685904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02589349414269812,"score_gpt":0.2516837427380955,"score_spread":0.2257902485953973,"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."}}