{"id":"W2018658758","doi":"10.1046/j.1365-2478.2001.00291.x","title":"Vibroseis deconvolution: a comparison of cross‐correlation and frequency‐domain sweep deconvolution","year":2001,"lang":"en","type":"article","venue":"Geophysical Prospecting","topic":"Machine Fault Diagnosis Techniques","field":"Engineering","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Seismic vibrator; Deconvolution; Wavelet; Blind deconvolution; Cross-correlation; Frequency domain; Signal processing; Computer science; Geology; Algorithm; Mathematics; Telecommunications; Seismology; Statistics; Artificial intelligence; Computer vision","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":[0.004231606,0.0008572535,0.0007916021,0.002770693,0.0004999159,0.001758664,0.001053683,0.001242582,0.002147508],"category_scores_gemma":[0.01028695,0.0003731645,0.0005190933,0.001934339,0.0008169934,0.002665727,0.001428914,0.000733513,0.000738933],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006256617,"about_ca_system_score_gemma":0.0015402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002290887,"about_ca_topic_score_gemma":0.002638603,"domain_scores_codex":[0.9985716,0.0002691837,0.00006017021,0.0001743462,0.0008173586,0.000107351],"domain_scores_gemma":[0.9948471,0.002508709,0.0003593737,0.00055283,0.001593781,0.0001382328],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002990454,0.0004141468,0.01066418,0.0008492266,0.0004632733,0.0002714099,0.0005535874,0.07604023,0.06351132,0.02646596,0.003286328,0.81449],"study_design_scores_gemma":[0.0001405472,0.0005465691,0.01736527,0.0001600233,0.0002380671,0.001637297,0.0003562367,0.7833115,0.1776869,0.00708972,0.01129104,0.000176836],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1138008,0.002726818,0.870729,0.0003046054,0.0001376693,0.0001307775,0.0001749115,0.002765723,0.009229762],"genre_scores_gemma":[0.4311163,0.002770001,0.5580572,0.0002052027,0.00008879902,0.0001091408,0.00063883,0.001094845,0.00591969],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004231606,"threshold_uncertainty_score":0.0223791,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01001962033208252,"score_gpt":0.2977832118007416,"score_spread":0.2877635914686591,"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."}}