{"id":"W4409528538","doi":"10.1016/j.jobe.2025.112641","title":"Comparative analysis of multi-stage filtration methods for crack detection in masonry structures","year":2025,"lang":"en","type":"article","venue":"Journal of Building Engineering","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Concordia University","funders":"National Research Foundation of Korea","keywords":"Masonry; Structural engineering; Stage (stratigraphy); Materials science; Composite material; Forensic engineering; Geotechnical engineering; Engineering; Geology","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":[0.000371097,0.0001192101,0.0004271786,0.00105039,0.00001884235,0.00001942444,0.0001008279,0.00007211166,0.000002381303],"category_scores_gemma":[0.0001289746,0.0001143521,0.0001610679,0.0007018151,0.000007463601,0.0001603658,0.000009639579,0.000216525,1.517836e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001474625,"about_ca_system_score_gemma":0.00001394319,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005482085,"about_ca_topic_score_gemma":0.00001106965,"domain_scores_codex":[0.9992194,0.00001664805,0.0004696143,0.0000735806,0.00007167808,0.0001490807],"domain_scores_gemma":[0.9994765,0.000182837,0.0001247081,0.00008165443,0.0001102356,0.00002406803],"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":[0.00001122293,0.000002946916,0.0002215022,0.0000808391,0.0003081993,6.38817e-7,0.0002010882,0.6621594,0.3327988,0.0001635807,0.000004723423,0.004047044],"study_design_scores_gemma":[0.0002570767,0.00001687754,0.01179345,0.00008160309,0.000153786,0.000001394754,0.0001058395,0.6410943,0.3460491,0.00004875609,0.0003285652,0.00006933789],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3290535,0.0003199213,0.6699013,0.000002491009,0.0006270135,0.00006135987,0.000002576625,0.00001706385,0.00001482398],"genre_scores_gemma":[0.7454152,0.00001656536,0.2544934,0.000002095175,0.00005445791,0.000003714954,7.564461e-7,0.000007423318,0.000006306134],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.4163617,"threshold_uncertainty_score":0.4663143,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02375025304987119,"score_gpt":0.354750821979379,"score_spread":0.3310005689295077,"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."}}