{"id":"W4401540811","doi":"10.1109/icphm61352.2024.10626846","title":"ICPHM’23 Benchmark Vibration Dataset Applicable in Machine Learning for Systems’ Health Monitoring","year":2024,"lang":"en","type":"article","venue":"","topic":"Structural Health Monitoring Techniques","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Benchmark (surveying); Computer science; Vibration; Artificial intelligence; Machine learning; Acoustics; Geology; Physics","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":[0.001260316,0.002056923,0.001211707,0.001729139,0.0006043657,0.0007864786,0.002833054,0.002264094,0.005404716],"category_scores_gemma":[0.003040077,0.0003556698,0.001269503,0.00184565,0.0005424615,0.0006775784,0.001366382,0.001347348,0.003849014],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009467491,"about_ca_system_score_gemma":0.001182595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01084865,"about_ca_topic_score_gemma":0.01892621,"domain_scores_codex":[0.9989159,0.0001752339,0.0001233087,0.0002691409,0.0003831233,0.0001332722],"domain_scores_gemma":[0.9989678,0.0002742597,0.00009816471,0.0002839688,0.0002961512,0.00007971098],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001251771,0.00138754,0.01261063,0.003682725,0.0005294495,0.0008279449,0.0001340504,0.117759,0.0145981,0.002600227,0.667332,0.1772866],"study_design_scores_gemma":[0.0009977795,0.002553663,0.1025351,0.0005519203,0.0002659278,0.001829208,0.0003966963,0.561345,0.02827021,0.01038124,0.2904906,0.0003827144],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.116258,0.005000528,0.05928746,0.0014169,0.001341049,0.001405611,0.7861094,0.0198606,0.009320503],"genre_scores_gemma":[0.09526525,0.0006337717,0.02856295,0.0002372262,0.0000966928,0.001193669,0.8708452,0.0002522417,0.002912997],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01084865,"threshold_uncertainty_score":0.02157098,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02717003193226046,"score_gpt":0.3254435151659298,"score_spread":0.2982734832336693,"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."}}