{"id":"W6983591714","doi":"","title":"MS/MS Spectrum Prediction for MHC-Associated Peptides with a Fine-Tuned Model","year":2024,"lang":"en","type":"dissertation","venue":"UWSpace (University of Waterloo)","topic":"Botanical Studies and Applications","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Blackberry (Canada)","funders":"","keywords":"Spectrum (functional analysis); Set (abstract data type); Training set; Quality (philosophy); Representation (politics); Deep learning; Transfer of learning; Spectral line","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006860396,0.0001864423,0.0002875273,0.000008837524,0.0003832295,0.00002981445,0.0002197471,0.000216007,0.0001097532],"category_scores_gemma":[0.000007358317,0.00008917879,0.0001867704,0.0002467647,0.00005297461,0.0000753334,0.00003969706,0.0001507894,0.0000176605],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000676325,"about_ca_system_score_gemma":0.0000100458,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.01663529,"about_ca_topic_score_gemma":0.5321633,"domain_scores_codex":[0.9990872,0.00001234,0.0001062111,0.0003785388,0.0001800548,0.0002356868],"domain_scores_gemma":[0.9995541,0.00005439787,0.0001483815,0.00006100012,0.0001149993,0.00006710117],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"qualitative","study_design_scores_codex":[0.007173277,0.004029071,0.005853559,0.002913145,0.006055073,0.00006953953,0.1387299,0.002316796,0.4668511,0.01128271,0.2507226,0.1040033],"study_design_scores_gemma":[0.006652672,0.01114115,0.2710058,0.004570918,0.00688488,0.00001072292,0.4686449,0.09119593,0.01214045,0.02665176,0.09511524,0.00598565],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9933286,0.00007503147,0.000008331303,0.004831603,0.00006839748,0.000473633,0.0006647496,0.0001097251,0.0004399463],"genre_scores_gemma":[0.6937504,0.0001597756,0.0003029995,0.00001701862,0.0001029584,0.000009011559,0.002364347,0.000004615317,0.3032889],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.515528,"threshold_uncertainty_score":0.989913,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01283340714836887,"score_gpt":0.187353377829476,"score_spread":0.1745199706811071,"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."}}