{"id":"W1977839424","doi":"10.1002/jms.1921","title":"It is time for a paradigm shift in drug discovery bioanalysis: from SRM to HRMS","year":2011,"lang":"en","type":"article","venue":"Journal of Mass Spectrometry","topic":"Analytical Chemistry and Chromatography","field":"Chemistry","cited_by":184,"is_retracted":false,"has_abstract":true,"ca_institutions":"Sciex (Canada); Spinal Cord Injury BC","funders":"","keywords":"Bioanalysis; Chemistry; Mass spectrometry; Chromatography; Drug discovery; Quadrupole time of flight; Resolution (logic); Tandem mass spectrometry; Triple quadrupole mass spectrometer; Qualitative analysis; Liquid chromatography–mass spectrometry; High-performance liquid chromatography; Nanotechnology; Analytical Chemistry (journal); Selected reaction monitoring; Computer science; Artificial intelligence","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002782644,0.0002622884,0.000667928,0.0003703439,0.00004496075,0.00007900228,0.0005912091,0.0001545511,0.005605072],"category_scores_gemma":[0.00008990717,0.0002231677,0.0007076513,0.0007150315,0.0000609303,0.0002946517,0.00005047859,0.0004203759,0.00004904239],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001368176,"about_ca_system_score_gemma":0.00006726178,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004008206,"about_ca_topic_score_gemma":0.00001747692,"domain_scores_codex":[0.9980075,0.00001559076,0.0008177056,0.0003159941,0.0004252772,0.0004179763],"domain_scores_gemma":[0.9986945,0.0001941359,0.0004002646,0.0003733108,0.00004135313,0.0002964036],"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":[0.004494151,0.004033338,0.1331739,0.0007040271,0.007656055,0.001338286,0.008251642,0.0000402041,0.7632179,0.00316274,0.07339737,0.0005303892],"study_design_scores_gemma":[0.002964359,0.0002658575,0.004356814,0.0005598436,0.001095214,0.00005458197,0.00148983,0.0002156954,0.8471909,0.1319882,0.008802634,0.001016088],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9553283,0.0008196497,0.005584376,0.004443949,0.00009109409,0.00008496182,0.0001775931,0.00003082286,0.03343925],"genre_scores_gemma":[0.9939027,0.00005146938,0.004174988,0.0005678173,0.0004261765,0.000005395947,0.00001062281,0.00002996397,0.000830797],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1288254,"threshold_uncertainty_score":0.9953039,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01249207749380509,"score_gpt":0.2359695307340636,"score_spread":0.2234774532402585,"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."}}