{"id":"W2063486872","doi":"10.1007/s00216-012-6192-3","title":"Peptide sequencing challenge","year":2012,"lang":"en","type":"article","venue":"Analytical and Bioanalytical Chemistry","topic":"Genetics, Bioinformatics, and Biomedical Research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"National Research Council Canada","funders":"","keywords":"Computer science; Nanotechnology; Library science; 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":[0.01580742,0.001197847,0.001741025,0.001084554,0.001998879,0.004499556,0.004224669,0.004495415,0.01989325],"category_scores_gemma":[0.01775114,0.0008250562,0.001045313,0.001098481,0.001609412,0.005682212,0.005025352,0.008234018,0.01672074],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001528579,"about_ca_system_score_gemma":0.005189432,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001332821,"about_ca_topic_score_gemma":0.002546404,"domain_scores_codex":[0.9911677,0.001350914,0.0003253554,0.002418258,0.003836449,0.0009012757],"domain_scores_gemma":[0.976545,0.008191062,0.0007555238,0.003205758,0.007855542,0.003447089],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001250739,0.0003356596,0.002619724,0.00161344,0.0001981248,0.001271142,0.0006438724,0.004539966,0.1136208,0.08759214,0.4932276,0.2930868],"study_design_scores_gemma":[0.0001215288,0.0003188311,0.001701729,0.0002790176,0.00006894815,0.002456662,0.0005801008,0.01499102,0.03958569,0.1125851,0.8271989,0.0001124982],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05616698,0.01929456,0.4928625,0.2265147,0.02809147,0.0009387014,0.01205034,0.01147722,0.1526036],"genre_scores_gemma":[0.1802486,0.0208715,0.4526983,0.1635671,0.01940314,0.002114558,0.03350693,0.00511617,0.1224737],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01989325,"threshold_uncertainty_score":0.08359861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02914863576616628,"score_gpt":0.2888318212873978,"score_spread":0.2596831855212315,"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."}}