{"id":"W2062123859","doi":"10.1366/0003702053945985","title":"Investigation of Selected Baseline Removal Techniques as Candidates for Automated Implementation","year":2005,"lang":"en","type":"article","venue":"Applied Spectroscopy","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":320,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Baseline (sea); Computer science; Environmental science; Political 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":[0.002830495,0.000854274,0.000557103,0.00192164,0.0005413701,0.001684121,0.001494333,0.0008522905,0.002337253],"category_scores_gemma":[0.008476666,0.0003972936,0.0005017127,0.001579184,0.0005540279,0.001357282,0.0007471147,0.0005710887,0.001059528],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004240953,"about_ca_system_score_gemma":0.0007645138,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004967523,"about_ca_topic_score_gemma":0.0009442955,"domain_scores_codex":[0.9987286,0.0003441222,0.0000777542,0.0002701261,0.0004828354,0.00009665949],"domain_scores_gemma":[0.9943567,0.003058702,0.000554346,0.0007252289,0.001211772,0.00009319572],"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":[0.0003283321,0.0003632476,0.005971628,0.0014081,0.0001268382,0.000251715,0.0003782808,0.03082479,0.1453026,0.01461995,0.001614096,0.7988103],"study_design_scores_gemma":[0.000142736,0.001610622,0.01185309,0.0003165719,0.0002106884,0.00113133,0.0005717782,0.516928,0.4233183,0.01219835,0.03159804,0.0001205354],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09318535,0.002690097,0.8963583,0.0003366376,0.00005191702,0.0002894578,0.0001312622,0.001956042,0.005001091],"genre_scores_gemma":[0.24687,0.001585316,0.7492043,0.00006665339,0.00003851941,0.0001905857,0.0002529343,0.000201996,0.00158973],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002830495,"threshold_uncertainty_score":0.01496923,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01079070597794205,"score_gpt":0.2780782205751618,"score_spread":0.2672875145972198,"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."}}