{"id":"W2011163417","doi":"10.1021/pr0501970","title":"Characterization of Human Tear Proteome Using Multiple Proteomic Analysis Techniques","year":2005,"lang":"en","type":"article","venue":"Journal of Proteome Research","topic":"Ocular Surface and Contact Lens","field":"Medicine","cited_by":148,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Proteome; Glycosylation; Proteomics; Computational biology; Biological fluids; Chemistry; Biomarker discovery; Chromatography; Bioinformatics; Biology; Biochemistry; Gene","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":[0.003156767,0.0001467918,0.0006581623,0.00174012,0.0001485149,0.00004331622,0.0002388261,0.0001624721,0.00017067],"category_scores_gemma":[0.0003215979,0.0001163728,0.0003533499,0.001464374,0.0001202993,0.0003821828,0.0000796712,0.0008755352,0.000009780492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003046863,"about_ca_system_score_gemma":0.0003912648,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008380052,"about_ca_topic_score_gemma":0.00001068629,"domain_scores_codex":[0.9969298,0.0003171263,0.0008519577,0.0001958059,0.001313947,0.0003914205],"domain_scores_gemma":[0.9972601,0.00003420169,0.0005472795,0.0003676181,0.001600312,0.0001904959],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002909181,0.000310466,0.05192151,0.0001812002,0.0004260584,0.00003537269,0.0002312761,0.000008397767,0.9445449,0.00001142398,0.000003090348,0.002035397],"study_design_scores_gemma":[0.0008254765,0.001181815,0.04452873,0.0003952622,0.0002589097,0.00003555156,0.00007632209,0.001085021,0.9510353,0.00003306242,0.0004369351,0.0001075877],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9939997,0.00006301101,0.003047675,0.0007590824,0.00001279065,0.001980118,0.000006244283,0.00001830889,0.0001130392],"genre_scores_gemma":[0.9822575,0.00004767736,0.0167825,0.00001704558,0.0004157558,0.00004071979,0.000007350964,0.00003077469,0.0004006497],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01373483,"threshold_uncertainty_score":0.4745543,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07986276021942393,"score_gpt":0.4080520240107023,"score_spread":0.3281892637912783,"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."}}