{"id":"W2109866814","doi":"10.1002/rcm.7222","title":"Establishment of tandem mass spectrometric fingerprint of novel antineoplastic curcumin analogues using electrospray ionization","year":2015,"lang":"en","type":"article","venue":"Rapid Communications in Mass Spectrometry","topic":"Curcumin's Biomedical Applications","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Chemistry; Tandem mass spectrometry; Electrospray ionization; Mass spectrometry; Collision-induced dissociation; Triple quadrupole mass spectrometer; Molecule; Electrospray; Quadrupole ion trap; Dissociation (chemistry); Fragmentation (computing); Top-down proteomics; Ion trap; Analytical Chemistry (journal); Chromatography; Selected reaction monitoring; Organic chemistry","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":[],"consensus_categories":[],"category_scores_codex":[0.0007702981,0.0002064201,0.0003687798,0.0009136332,0.00006802832,0.00002153861,0.001055864,0.0001824837,0.00002551355],"category_scores_gemma":[0.0007921322,0.0002245131,0.0001038004,0.003617183,0.0003336397,0.00001680835,0.0003389416,0.0002487755,0.000002531446],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001947681,"about_ca_system_score_gemma":0.0002956886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000794125,"about_ca_topic_score_gemma":0.00002868362,"domain_scores_codex":[0.9980323,0.0001312903,0.0007599355,0.0003676731,0.0003818737,0.0003269064],"domain_scores_gemma":[0.9972629,0.0001440875,0.0004720023,0.001670004,0.0003282199,0.000122796],"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":[0.00002260618,0.0006475689,0.0246198,0.00002600598,0.00006560367,2.677394e-7,0.00005190446,0.0003672907,0.9705172,0.003259365,0.00007974828,0.0003426351],"study_design_scores_gemma":[0.003221611,0.0009990288,0.03509076,0.0001424084,0.0001550017,0.00003749477,0.0005686109,0.023497,0.929055,0.003382818,0.003099822,0.0007503801],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.4976167,0.003061187,0.4968753,0.0003945534,0.00007858583,0.0004061369,0.00006061318,0.00002366125,0.001483318],"genre_scores_gemma":[0.8486009,0.0006131618,0.1503242,0.0000179721,0.00005354645,0.00002901878,0.0003114519,0.00002532843,0.00002445699],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3509842,"threshold_uncertainty_score":0.9155377,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04056954250321163,"score_gpt":0.3063703674309761,"score_spread":0.2658008249277645,"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."}}