{"id":"W6926223566","doi":"10.25345/c5sx64m1f","title":"MassIVE MSV000092164 - Functional proteomics analyses of human PHRF1","year":2023,"lang":"en","type":"dataset","venue":"UC San Diego","topic":"Educational Games and Gamification","field":"Psychology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université Laval","funders":"","keywords":"Proteomics; Identification (biology); Human genome; Functional genomics","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":[0.000986472,0.002167743,0.001503685,0.002425214,0.001238679,0.001618154,0.002076149,0.002119182,0.02953256],"category_scores_gemma":[0.002685965,0.0005678553,0.001161202,0.00314243,0.0003665883,0.000622609,0.001683383,0.001429828,0.03303785],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009676278,"about_ca_system_score_gemma":0.002182142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01682536,"about_ca_topic_score_gemma":0.03288969,"domain_scores_codex":[0.9993188,0.00006912697,0.00004986984,0.0002423129,0.0001809532,0.0001388767],"domain_scores_gemma":[0.9992137,0.0002396387,0.00006874066,0.0001755554,0.0001753193,0.0001270464],"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":[0.0006573414,0.0001120037,0.005153736,0.001373266,0.0001903555,0.0002542801,0.00009734338,0.0009108535,0.005799491,0.001286957,0.9749502,0.009214235],"study_design_scores_gemma":[0.001135247,0.0001348628,0.04010983,0.0005390797,0.0003353076,0.0007486507,0.0002604844,0.002986299,0.007129841,0.006602914,0.9398903,0.0001271926],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003869159,0.0004610498,0.0004108139,0.0001775898,0.00006195765,0.00002501049,0.9909649,0.001488726,0.002540791],"genre_scores_gemma":[0.002985259,0.0001401517,0.0009259969,0.0001109327,0.000009313266,0.000070222,0.9946391,0.0001637836,0.0009552933],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02953256,"threshold_uncertainty_score":0.09879625,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1150311836649145,"score_gpt":0.4154696125681384,"score_spread":0.3004384289032239,"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."}}