{"id":"W6967566636","doi":"10.5281/zenodo.10581948","title":"ATR phosphoproteomics","year":2023,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Phosphoproteomics; Identification (biology); Proteome","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":[0.004095277,0.0041695,0.003572269,0.003049516,0.00176989,0.004921257,0.00356813,0.001346221,0.1336678],"category_scores_gemma":[0.007169221,0.001726368,0.002879692,0.002593131,0.0006561724,0.002185673,0.003053799,0.003907829,0.1539217],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001173383,"about_ca_system_score_gemma":0.002789457,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002973508,"about_ca_topic_score_gemma":0.004452303,"domain_scores_codex":[0.9977336,0.0004250803,0.000220174,0.000950184,0.0004613156,0.000209583],"domain_scores_gemma":[0.9981635,0.0005347387,0.0001907036,0.0005863002,0.0004012709,0.0001234456],"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":[0.001743021,0.0001278189,0.003398052,0.004458944,0.001009275,0.00041285,0.0002891063,0.001845044,0.02617121,0.004901444,0.9148894,0.04075377],"study_design_scores_gemma":[0.0009682418,0.0001953602,0.00819766,0.0006158286,0.0006228599,0.00118889,0.0001872509,0.0132962,0.03740431,0.01795806,0.9190506,0.0003147685],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.004710722,0.001264403,0.09284381,0.0005156847,0.0004479605,0.0008014251,0.674399,0.2144698,0.01054713],"genre_scores_gemma":[0.01452617,0.0009233289,0.1831963,0.001329704,0.0001397166,0.003875023,0.6929272,0.08802727,0.01505531],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1336678,"threshold_uncertainty_score":0.4471634,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03043008779162948,"score_gpt":0.2657224538908711,"score_spread":0.2352923660992416,"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."}}