{"id":"W4400499654","doi":"10.55037/lxlaser.21st.189","title":"Assessing The Potential Of PIV Data To Resolve Hidden Frequency Scales","year":2024,"lang":"en","type":"article","venue":"","topic":"Risk and Safety Analysis","field":"Decision Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Computer science; Data science","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":[0.003004774,0.0007527658,0.0004657255,0.0009481406,0.0004051684,0.001070331,0.0007283887,0.001273001,0.001069066],"category_scores_gemma":[0.01267767,0.0003429894,0.0003240068,0.0005807296,0.0005019163,0.001529046,0.00102456,0.0006461519,0.0003293662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002823704,"about_ca_system_score_gemma":0.0004636596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001556598,"about_ca_topic_score_gemma":0.001371006,"domain_scores_codex":[0.9991084,0.0002940045,0.00005052916,0.000124571,0.0002976489,0.0001249257],"domain_scores_gemma":[0.9916399,0.00630538,0.0003920575,0.00073123,0.000814041,0.0001173534],"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":[0.003068358,0.0008789007,0.06033086,0.0009775609,0.0002875097,0.0005950568,0.0005701804,0.4113427,0.1880731,0.007940267,0.001044502,0.3248911],"study_design_scores_gemma":[0.00002666222,0.0007340926,0.01509442,0.00003812876,0.00005464089,0.0001957355,0.0001513413,0.9131833,0.06799117,0.001479265,0.0009864621,0.00006476222],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6905312,0.0007950211,0.3042076,0.0002478449,0.0001047727,0.0001158428,0.0003620385,0.0005343443,0.003101297],"genre_scores_gemma":[0.9470347,0.0001660116,0.05205738,0.00002785432,0.00001645975,0.00002977738,0.000204202,0.00004272578,0.0004208936],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003004774,"threshold_uncertainty_score":0.01589096,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2022460415993662,"score_gpt":0.4595619733760064,"score_spread":0.2573159317766402,"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."}}