{"id":"W2055487532","doi":"10.1007/bf02427958","title":"Surface profiling using sequential sampling and inverse methods. Part I: Mathematical background","year":2004,"lang":"en","type":"article","venue":"Experimental Mechanics","topic":"Railway Engineering and Dynamics","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Profiling (computer programming); Solid mechanics; Inverse problem; Inverse; Sampling (signal processing); Mathematics; Computer science; Materials science; Mathematical analysis; Geometry; Composite material; Computer vision","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":[0.0008914953,0.000810959,0.000617639,0.0009941752,0.000291332,0.0007446507,0.0009732799,0.0007730887,0.002990165],"category_scores_gemma":[0.002726628,0.0006113758,0.0006014308,0.001375867,0.001006947,0.001807695,0.001011002,0.0008613309,0.0006660282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00039053,"about_ca_system_score_gemma":0.0006593513,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002051098,"about_ca_topic_score_gemma":0.001451544,"domain_scores_codex":[0.9994774,0.0001209238,0.00004079166,0.0001105932,0.0002194912,0.00003082465],"domain_scores_gemma":[0.9993302,0.0003651171,0.00006736419,0.00009196641,0.0001291235,0.00001632815],"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":[0.0001465256,0.0001809154,0.002178415,0.001718654,0.00007498507,0.0002496325,0.0003206468,0.1827821,0.07049534,0.4214916,0.005029595,0.3153315],"study_design_scores_gemma":[0.00002233539,0.0001545799,0.001621997,0.0001094841,0.00002799085,0.0005074296,0.00006473163,0.8568404,0.01377547,0.09525567,0.0315714,0.00004857393],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003819285,0.001983148,0.9906205,0.0001725234,0.0001029204,0.00004477351,0.00006951138,0.00007437149,0.003112972],"genre_scores_gemma":[0.2046346,0.01257206,0.768301,0.000141855,0.0007322856,0.0004372802,0.0004496867,0.000129248,0.01260193],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002990165,"threshold_uncertainty_score":0.01000309,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06817309855659341,"score_gpt":0.3316503584595943,"score_spread":0.2634772599030009,"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."}}