{"id":"W1565936142","doi":"10.1089/omi.2013.0176","title":"HFIP Extraction Followed by 2D CTAB/SDS-PAGE Separation: A New Methodology for Protein Identification from Tissue Sections after MALDI Mass Spectrometry Profiling for Personalized Medicine Research","year":2014,"lang":"en","type":"article","venue":"OMICS A Journal of Integrative Biology","topic":"Mass Spectrometry Techniques and Applications","field":"Chemistry","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"Agence Nationale de la Recherche; Prostate Cancer Canada; Movember Foundation","keywords":"Chromatography; Mass spectrometry; Matrix-assisted laser desorption/ionization; Biomarker discovery; Chemistry; Protein purification; Mass spectrometry imaging; Proteomics; Biochemistry; Desorption","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002406832,0.0002518724,0.0006174296,0.0004019906,0.0002333913,0.00005188122,0.0003544964,0.0003836384,0.001121173],"category_scores_gemma":[0.002302409,0.0001930674,0.0002206881,0.0003817298,0.0002314901,0.0001421039,0.00002665376,0.0006860439,0.000003776088],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003779188,"about_ca_system_score_gemma":0.0001710499,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001131279,"about_ca_topic_score_gemma":0.00004604939,"domain_scores_codex":[0.997724,0.0003663893,0.0009028589,0.0004568505,0.0001913854,0.0003585424],"domain_scores_gemma":[0.9960322,0.00167811,0.0008511638,0.0003021855,0.0009941601,0.0001421292],"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":[0.0008762602,0.00007504269,0.0001172426,0.00003100897,0.0001368912,5.375455e-7,0.0002480776,9.07847e-7,0.9378439,0.05546628,0.004003306,0.001200557],"study_design_scores_gemma":[0.00115639,0.0008178338,0.00001850375,0.00006169151,0.00008566249,0.00002532352,0.0007884809,0.0004721795,0.8127741,0.1130179,0.0706234,0.0001585651],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0912523,0.0007418804,0.9022111,0.003618528,0.0001909986,0.0008193869,0.0002633067,0.00003407068,0.0008684663],"genre_scores_gemma":[0.5861809,0.0001414103,0.404624,0.00005879648,0.001614164,0.001012591,0.0004325585,0.0000454677,0.005890121],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4975871,"threshold_uncertainty_score":0.9997919,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08143612550394566,"score_gpt":0.4433361950923967,"score_spread":0.361900069588451,"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."}}