{"id":"W1989308650","doi":"10.1021/es200203z","title":"Universally Applicable Model for the Quantitative Determination of Lake Sediment Composition Using Fourier Transform Infrared Spectroscopy","year":2011,"lang":"en","type":"article","venue":"Environmental Science & Technology","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":48,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Canadian Institutes of Health Research","keywords":"Absorbance; Total organic carbon; Dissolved organic carbon; Calibration; Sediment; Spectroscopy; Infrared spectroscopy; Fourier transform infrared spectroscopy; Colored dissolved organic matter; Robustness (evolution); Infrared; Environmental science; Mineralogy; Chemistry; Geology; Analytical Chemistry (journal); Environmental chemistry; Optics; Mathematics; Geomorphology; Physics; Statistics; Chromatography; Organic chemistry","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.001869377,0.00128088,0.0006746488,0.0008240231,0.0003876624,0.0008734438,0.001524184,0.001378158,0.001689643],"category_scores_gemma":[0.004096751,0.0004568576,0.0009481329,0.0005482198,0.0006722452,0.0009315357,0.00081068,0.001227665,0.0006387128],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001646549,"about_ca_system_score_gemma":0.001259486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0215147,"about_ca_topic_score_gemma":0.009720114,"domain_scores_codex":[0.9993243,0.0001808624,0.00002554482,0.0002378308,0.0001495916,0.00008189746],"domain_scores_gemma":[0.9988686,0.0006135253,0.0001677365,0.00005948303,0.0002696713,0.00002097025],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001726296,0.00001620045,0.001041638,0.00002077346,0.00002585452,0.0000259027,0.00002399724,0.9881663,0.001036758,0.00277568,0.0002383531,0.006611275],"study_design_scores_gemma":[0.000003054794,0.000006631594,0.0002472046,0.000003340266,0.000005044098,0.000006809673,0.000002964713,0.9978992,0.0003040219,0.001299405,0.0002170603,0.000005378835],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.05671971,0.0002398737,0.9367594,0.0001695369,0.00003566159,0.00009554674,0.0004920748,0.001037484,0.004450875],"genre_scores_gemma":[0.8849162,0.0003221469,0.1050468,0.000152554,0.00002934105,0.0007630433,0.001043295,0.000204624,0.007521973],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0215147,"threshold_uncertainty_score":0.04277897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02095782175511545,"score_gpt":0.2344137006868411,"score_spread":0.2134558789317256,"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."}}