{"id":"W4379054304","doi":"10.3390/mi14061174","title":"PreOBP_ML: Machine Learning Algorithms for Prediction of Optical Biosensor Parameters","year":2023,"lang":"en","type":"article","venue":"Micromachines","topic":"Advanced Biosensing Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Multiphysics; Algorithm; Mean squared error; Elastic net regularization; Lasso (programming language); Computer science; Biosensor; Machine learning; Artificial intelligence; Mathematics; Feature selection; Materials science; Engineering; Statistics; Nanotechnology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001922376,0.001845133,0.001059506,0.001007571,0.0005062842,0.001006532,0.001640032,0.001635305,0.006003898],"category_scores_gemma":[0.006236221,0.0007823227,0.0009703744,0.0007702227,0.0004930532,0.001023571,0.001103343,0.002993844,0.001864448],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006196677,"about_ca_system_score_gemma":0.001309326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003408424,"about_ca_topic_score_gemma":0.003304614,"domain_scores_codex":[0.9993876,0.0002096924,0.00004487745,0.0001327346,0.0001779083,0.0000472016],"domain_scores_gemma":[0.9976405,0.001710571,0.0001675942,0.0001462661,0.000292905,0.00004226221],"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":[0.0001350589,0.0001754818,0.001533931,0.0002484893,0.000126123,0.00006898409,0.00004832539,0.7906261,0.002626334,0.006592482,0.007651858,0.1901668],"study_design_scores_gemma":[0.000005405632,0.00001350648,0.00006802724,0.000008879107,0.000002865447,0.000006870205,0.000003233112,0.996637,0.0008187192,0.00163364,0.0007974893,0.000004344044],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004840016,0.0004541195,0.9884017,0.000253156,0.00005781091,0.0000712488,0.0003059749,0.004199953,0.001415887],"genre_scores_gemma":[0.1525435,0.0006887161,0.8389473,0.000350977,0.00009771472,0.001138877,0.001430802,0.00084924,0.003952824],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006003898,"threshold_uncertainty_score":0.02008498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02351424550160193,"score_gpt":0.2932858076104043,"score_spread":0.2697715621088024,"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."}}