{"id":"W2998243789","doi":"10.7717/peerj.8179","title":"The Rametrix<sup>™</sup> PRO Toolbox v1.0 for MATLAB<sup>®</sup>","year":2020,"lang":"en","type":"article","venue":"PeerJ","topic":"Spectroscopy Techniques in Biomedical and Chemical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Hatch","keywords":"Toolbox; Principal component analysis; MATLAB; Computer science; Raman spectroscopy; Sensitivity (control systems); Artificial intelligence; Pattern recognition (psychology); Linear discriminant analysis; False positive paradox; Machine learning; Data mining; Chemistry; Physics; Optics","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.002296989,0.002386084,0.001356143,0.001442508,0.000468019,0.002349603,0.002983348,0.0009942382,0.1325224],"category_scores_gemma":[0.009606712,0.0009487759,0.001485807,0.001327324,0.0006875313,0.001700399,0.001849696,0.002381693,0.09049878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006119419,"about_ca_system_score_gemma":0.00168397,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002046022,"about_ca_topic_score_gemma":0.002771638,"domain_scores_codex":[0.9988256,0.0002130334,0.0001407565,0.0002809229,0.0004111287,0.0001284978],"domain_scores_gemma":[0.9970964,0.001353468,0.0002934236,0.0003813853,0.0007668284,0.0001085183],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008912279,0.0001561536,0.00256876,0.003810743,0.0002999727,0.0007365945,0.0004347854,0.02851282,0.01977544,0.01938743,0.7095803,0.2138458],"study_design_scores_gemma":[0.0004069829,0.0003105619,0.006791804,0.001011703,0.0002131855,0.001436175,0.0002397211,0.2168797,0.05623612,0.04487552,0.6712239,0.0003746543],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.004384997,0.001020653,0.5446819,0.0006102273,0.0002872518,0.0002992526,0.05846549,0.3725549,0.01769529],"genre_scores_gemma":[0.04212597,0.001813622,0.6612981,0.001684462,0.0001728947,0.00260611,0.1187751,0.1443759,0.02714781],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.1325224,"threshold_uncertainty_score":0.4433315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02340156295391806,"score_gpt":0.3270153645928056,"score_spread":0.3036138016388875,"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."}}