{"id":"W2008729476","doi":"10.1021/ie061348r","title":"Use of Wavelet Packet Transform in Characterization of Surface Quality","year":2007,"lang":"en","type":"article","venue":"Industrial & Engineering Chemistry Research","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"McMaster University","keywords":"Wavelet packet decomposition; Discrete wavelet transform; Second-generation wavelet transform; Wavelet; Wavelet transform; Stationary wavelet transform; Pattern recognition (psychology); Lifting scheme; Computer science; Harmonic wavelet transform; Artificial intelligence; Feature extraction; Mathematics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001500361,0.0005490574,0.0005004644,0.001821218,0.0001644226,0.0008874886,0.0004086389,0.0006603109,0.0005217387],"category_scores_gemma":[0.003270403,0.0002047447,0.0004808261,0.002756382,0.0006184245,0.001322881,0.0003662376,0.0008889036,0.0003257503],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002401634,"about_ca_system_score_gemma":0.0002437699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008049629,"about_ca_topic_score_gemma":0.000361966,"domain_scores_codex":[0.9993673,0.0001392769,0.00003623992,0.00009427842,0.0003177379,0.00004524141],"domain_scores_gemma":[0.999035,0.000460351,0.0001120413,0.0001113027,0.0002588609,0.00002237565],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005165089,0.0001962776,0.007989801,0.0004214818,0.0001457325,0.0004487776,0.0002093317,0.09360473,0.1944429,0.01581593,0.001939194,0.6842694],"study_design_scores_gemma":[0.00003453488,0.000339581,0.01486315,0.00004163732,0.0000977036,0.0005956203,0.0001175728,0.8787429,0.09003237,0.01025661,0.004800498,0.00007779113],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09019852,0.001331212,0.9051162,0.0002189912,0.0001103734,0.00005790688,0.0001986162,0.0003428892,0.002425208],"genre_scores_gemma":[0.6667296,0.002586265,0.3290221,0.00008299475,0.0000978111,0.00005633181,0.0003538599,0.00006987758,0.001001067],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001821218,"threshold_uncertainty_score":0.007934809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2064984234298309,"score_gpt":0.3939064944857694,"score_spread":0.1874080710559386,"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."}}