{"id":"W1950720201","doi":"10.1002/dta.1727","title":"Direct analysis in real time ‐ high resolution mass spectrometry (DART‐HRMS): a high throughput strategy for identification and quantification of anabolic steroid esters","year":2014,"lang":"en","type":"article","venue":"Drug Testing and Analysis","topic":"Mass Spectrometry Techniques and Applications","field":"Chemistry","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"World Anti-Doping Agency","keywords":"DART ion source; Orbitrap; Chemistry; Chromatography; Mass spectrometry; Repeatability; Dart; Steroid; Hormone; Ion; Electron ionization; Computer science; Biochemistry","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001778221,0.001623976,0.0008971944,0.00121168,0.0003949101,0.001023156,0.001049661,0.001249027,0.001721996],"category_scores_gemma":[0.00146106,0.000450168,0.0005915829,0.0009616246,0.0008689144,0.001399494,0.001654274,0.001622237,0.002019684],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003671168,"about_ca_system_score_gemma":0.0007206083,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002459499,"about_ca_topic_score_gemma":0.0005119223,"domain_scores_codex":[0.9980392,0.0003896146,0.00008157939,0.0004692578,0.0009322236,0.00008821652],"domain_scores_gemma":[0.9991198,0.0002617355,0.0002080466,0.000107095,0.0002369039,0.00006640369],"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":[0.0001337599,0.00004123614,0.0006093596,0.0003027394,0.000065383,0.0001270675,0.00003157346,0.0001257978,0.9716321,0.0003375878,0.0003506776,0.02624273],"study_design_scores_gemma":[0.00002841654,0.0004240475,0.002021137,0.0000273518,0.0000837937,0.001727959,0.00005565758,0.003948554,0.9818065,0.0006109059,0.009214813,0.00005077486],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3037707,0.04685259,0.6317788,0.001074976,0.0009026811,0.0008692439,0.002593588,0.004266453,0.007891049],"genre_scores_gemma":[0.4615802,0.02985833,0.4926729,0.001552911,0.0005145167,0.0006120636,0.00217525,0.0003479909,0.01068575],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001778221,"threshold_uncertainty_score":0.009404242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01856610771981325,"score_gpt":0.274956349825463,"score_spread":0.2563902421056498,"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."}}