{"id":"W4377832633","doi":"10.18280/ts.400222","title":"Non Invasive Decay Analysis of Monument Using Deep Learning Techniques","year":2023,"lang":"en","type":"article","venue":"Traitement du signal","topic":"Geophysical Methods and Applications","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Artificial intelligence; Geology; Environmental science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001676158,0.00009717115,0.000202901,0.0002360773,0.00005154512,0.00001327345,0.00008957077,0.0000319844,0.0001091115],"category_scores_gemma":[0.000005998276,0.00009628515,0.0001175123,0.00112508,0.00001765263,0.00004252866,0.00002604578,0.00007909557,0.0000112455],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000325683,"about_ca_system_score_gemma":0.000005240335,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000265286,"about_ca_topic_score_gemma":0.000006899924,"domain_scores_codex":[0.9993307,0.00002018043,0.0002180759,0.0001235658,0.0001467635,0.0001606922],"domain_scores_gemma":[0.999679,0.0001026988,0.0000424484,0.0000987151,0.0000328114,0.00004432868],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000002095729,0.00002968954,0.001460616,0.00003819429,0.000391109,0.00000141763,0.0003755968,0.2791789,0.6983808,0.0002999925,0.00001465501,0.01982688],"study_design_scores_gemma":[0.00009544018,0.00005477047,0.03955025,0.00003643809,0.000521468,2.078294e-7,0.0002535473,0.6367258,0.3219758,0.0002566561,0.0003417532,0.0001878647],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.844565,0.00001385701,0.1545934,0.00001478371,0.0000132715,0.0001508228,0.000005572221,0.0002207931,0.0004225369],"genre_scores_gemma":[0.9858142,0.00002646692,0.01400461,0.000007608383,0.00003660641,0.00005995043,0.00002154617,0.00001511242,0.0000139501],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.376405,"threshold_uncertainty_score":0.3926394,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02233989202539828,"score_gpt":0.2778610352293429,"score_spread":0.2555211432039446,"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."}}