{"id":"W4401258543","doi":"10.22541/au.172259951.13322075/v1","title":"Filling the Gaps in Peptide Maps with a Platform Assay for Top-Down Characterization of Purified Protein Samples","year":2024,"lang":"en","type":"preprint","venue":"","topic":"Advanced Biosensing Techniques and Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"AbCellera (Canada)","funders":"","keywords":"Characterization (materials science); Peptide; Chemistry; Computational biology; Molecular biology; Nanotechnology; Biology; Biochemistry; Materials science","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":[0.001831599,0.0014621,0.001194909,0.001416053,0.0009245216,0.001454343,0.0008172009,0.001071992,0.003762412],"category_scores_gemma":[0.002360262,0.0006413436,0.0007062252,0.001241349,0.0006234596,0.00125872,0.001431532,0.001583839,0.002109769],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005363109,"about_ca_system_score_gemma":0.0008429957,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005755119,"about_ca_topic_score_gemma":0.001420987,"domain_scores_codex":[0.9982712,0.0001698748,0.000163121,0.0006396162,0.0005700182,0.0001861494],"domain_scores_gemma":[0.9984503,0.0005593332,0.0002029758,0.0003644879,0.0002612595,0.0001616656],"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":[0.0001758041,0.00005212161,0.0006104601,0.0001282385,0.00002728557,0.00008528323,0.00005822899,0.0001708205,0.9886692,0.0002507259,0.0003697871,0.009401989],"study_design_scores_gemma":[0.0000201785,0.0001857538,0.004709189,0.00003016527,0.00004768802,0.000374914,0.00005200841,0.007179738,0.9799759,0.0004425973,0.006957182,0.00002467994],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4744977,0.002205236,0.5074543,0.0004860402,0.0002489546,0.000468673,0.005218539,0.006374098,0.003046542],"genre_scores_gemma":[0.3144294,0.002310812,0.6614054,0.0005688453,0.00006378434,0.001622735,0.0135399,0.001537465,0.004521478],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003762412,"threshold_uncertainty_score":0.01258653,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0181124043733914,"score_gpt":0.2699908610358584,"score_spread":0.251878456662467,"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."}}