{"id":"W6911012862","doi":"10.5281/zenodo.10558293","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; Proteome; Identification (biology)","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":[0.003894438,0.004414672,0.003759708,0.003095836,0.001841233,0.004830693,0.003362425,0.001300958,0.1228074],"category_scores_gemma":[0.006361825,0.001728313,0.002866584,0.002622627,0.0006613911,0.002095098,0.002973257,0.003878453,0.1369948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001178597,"about_ca_system_score_gemma":0.002666614,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002769229,"about_ca_topic_score_gemma":0.004509369,"domain_scores_codex":[0.9979416,0.000360454,0.0002030708,0.0008915764,0.0004019275,0.0002013169],"domain_scores_gemma":[0.9984708,0.0004262761,0.0001674525,0.0004926004,0.0003315421,0.0001113558],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.002011962,0.0001489527,0.003772807,0.005279159,0.001105901,0.0004901152,0.0003389767,0.001883023,0.03301575,0.004929719,0.9078417,0.0391819],"study_design_scores_gemma":[0.001225732,0.0002231165,0.009271815,0.0006076692,0.000686346,0.001345962,0.0002069839,0.01410621,0.04481665,0.01814303,0.9090247,0.0003418271],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.005218908,0.001255026,0.08447329,0.0004495051,0.0003855127,0.0008086799,0.6828176,0.2154346,0.009156865],"genre_scores_gemma":[0.01503564,0.0008957629,0.1767312,0.001150544,0.0001240289,0.003879266,0.7076216,0.08167595,0.01288598],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1228074,"threshold_uncertainty_score":0.4108317,"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."}}