{"id":"W2156951240","doi":"10.1002/cem.2598","title":"Search prefilters for mid‐infrared absorbance spectra of clear coat automotive paint smears using stacked and linear classifiers","year":2014,"lang":"en","type":"article","venue":"Journal of Chemometrics","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Canadian Mounted Police","funders":"National Institute of Justice; Office of Justice Programs; U.S. Department of Justice","keywords":"Pattern recognition (psychology); Artificial intelligence; Principal component analysis; Wavelet; Computer science; Partial least squares regression; Spectral line; Stacking; Biological system; Mathematics; Physics; Machine learning; Biology; Nuclear magnetic resonance","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001039434,0.0002444691,0.000763673,0.001158611,0.00009557495,0.00005409788,0.0003710571,0.0002273226,0.0001300083],"category_scores_gemma":[0.002629798,0.0002230704,0.0003113328,0.002149708,0.0002312852,0.0002012015,0.00006713606,0.0005213161,0.000001052699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002944186,"about_ca_system_score_gemma":0.0001591807,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009619439,"about_ca_topic_score_gemma":3.005174e-7,"domain_scores_codex":[0.997753,0.00003954665,0.0008162153,0.0002668865,0.0006981404,0.0004262589],"domain_scores_gemma":[0.9968658,0.0008572852,0.0008975382,0.0002757221,0.0008532049,0.0002504695],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00153279,0.0007203456,0.01835273,0.002031247,0.001393431,0.00002471976,0.00143712,0.001457672,0.9638648,0.0002051277,0.002564018,0.006415988],"study_design_scores_gemma":[0.002136742,0.0005106098,0.0008715711,0.0001156359,0.0003821756,0.00005032363,0.001416707,0.009212683,0.9828316,0.0004104216,0.001783162,0.0002783702],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9748622,0.001055863,0.02220874,0.0001819325,0.0001124468,0.00008865874,0.00003081613,0.00002000188,0.001439391],"genre_scores_gemma":[0.9722523,0.0004015664,0.02635049,0.00008279983,0.0003393692,0.00000130912,0.000004699915,0.00004862537,0.0005188329],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01896678,"threshold_uncertainty_score":0.9096545,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04558494079940911,"score_gpt":0.31065437913857,"score_spread":0.2650694383391609,"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."}}