{"id":"W2222401202","doi":"","title":"Synchrotron-Based Microspectroscopic Analysis of Molecular and Biopolymer Structures Using Multivariate Techniques and Advanced Multi-Components Modeling","year":2008,"lang":"en","type":"article","venue":"Canadian journal of analytical sciences and spectroscopy","topic":"Spectroscopy Techniques in Biomedical and Chemical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Biopolymer; Synchrotron; Principal component analysis; Synchrotron radiation; Gaussian; Multivariate statistics; Biological system; Chemistry; Materials science; Computer science; Optics; Physics; Computational chemistry; Artificial intelligence; Biology; Machine learning; Polymer","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.00079742,0.0005965598,0.0003779442,0.001432349,0.0002551774,0.0005371647,0.0003513182,0.0003868553,0.001075316],"category_scores_gemma":[0.0007321373,0.000220772,0.0007799478,0.0009527372,0.0003823251,0.0006091876,0.0003610078,0.0005989536,0.0002983965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004258266,"about_ca_system_score_gemma":0.0005475876,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001944533,"about_ca_topic_score_gemma":0.002852413,"domain_scores_codex":[0.9996613,0.00007759692,0.00001898861,0.00006873185,0.0001558376,0.0000175237],"domain_scores_gemma":[0.9996112,0.0001832782,0.00005445073,0.00004314783,0.00009244202,0.00001553247],"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":[0.000128812,0.0001834555,0.005110449,0.0005884343,0.0001676424,0.0001313477,0.0002659599,0.09766174,0.5296203,0.01165639,0.001460583,0.3530249],"study_design_scores_gemma":[0.00001029823,0.00007418192,0.00981978,0.00001594945,0.00003819519,0.0001509529,0.00006450719,0.8847547,0.09767175,0.00390849,0.003422304,0.00006879694],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04283955,0.0003294591,0.9549728,0.00009181587,0.00001669013,0.00004248603,0.0001889719,0.0007920301,0.0007261679],"genre_scores_gemma":[0.2932526,0.0006706793,0.7040511,0.00004408175,0.0000390176,0.0001306063,0.0003869146,0.0001293598,0.001295614],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001944533,"threshold_uncertainty_score":0.004217207,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02950640585017756,"score_gpt":0.3370999347927988,"score_spread":0.3075935289426213,"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."}}