{"id":"W4295339011","doi":"10.26434/chemrxiv-2022-b97x0","title":"OpenPCA and Raman mapping to decipher complex spectral datasets from multi-component samples: application to cannabinoids and cannabis trichomes","year":2022,"lang":"en","type":"preprint","venue":"ChemRxiv","topic":"Spectroscopy and Chemometric Analyses","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Principal component analysis; Raman spectroscopy; Computer science; Pattern recognition (psychology); Biological system; Artificial intelligence; Pooling; Data mining; Biology; Physics; Optics","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":[0.001448003,0.001335315,0.0005145761,0.001696661,0.0005723087,0.001245745,0.000844376,0.0006904786,0.005216343],"category_scores_gemma":[0.004634097,0.0003974804,0.00098235,0.001533692,0.0006898774,0.001130033,0.001487112,0.001369235,0.001626952],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003622442,"about_ca_system_score_gemma":0.001046158,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002385286,"about_ca_topic_score_gemma":0.002971876,"domain_scores_codex":[0.9993718,0.0001481928,0.0000390546,0.0001637681,0.0002186747,0.00005847122],"domain_scores_gemma":[0.998672,0.0006288224,0.0001134695,0.0002490978,0.000266623,0.00006991161],"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":[0.0006444469,0.0003148099,0.004054333,0.0007338288,0.0002780411,0.0006987333,0.0008346195,0.05829987,0.3282199,0.02243968,0.01173723,0.5717444],"study_design_scores_gemma":[0.00004771242,0.0001023885,0.007337222,0.00005650169,0.00004403399,0.0005644614,0.000195419,0.7856868,0.1593822,0.0279345,0.01850181,0.0001468917],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02573653,0.0001798781,0.9620146,0.0003028697,0.00007583166,0.00007103434,0.0008350414,0.009476541,0.001307793],"genre_scores_gemma":[0.1347639,0.0004044872,0.8588836,0.0001223035,0.00004796957,0.0003024449,0.00159593,0.001902019,0.00197732],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005216343,"threshold_uncertainty_score":0.01745039,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05536077717590449,"score_gpt":0.3150258086259228,"score_spread":0.2596650314500183,"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."}}